📍 Job Overview

Job Title: Senior Data Platform Engineer (OpenMetadata) - GTM Data Leader
Company: Truelogic
Location: Dominican Republic
Job Type: Remote
Category: Data Engineering & Platform Development
Date Posted: August 9, 2025
Experience Level: 5-10 years

🚀 Role Summary

Metadata Management: Extend and optimize OpenMetadata platform, enhancing ingestion pipelines, data lineage capture, and integration with modern data stack (Airflow, RDS, OpenSearch).
Backend Development: Design, build, and maintain custom OpenMetadata connectors, debug, and enhance backend features for stability and scalability.
System Reliability: Manage containerized deployments, implement monitoring solutions, and ensure high-availability configurations.
Collaboration: Work closely with platform engineers, taking full ownership of feature development and operational stability for the metadata platform.

📝 Enhancement Note: This role requires a strong background in data engineering and platform development, with a specific focus on OpenMetadata. Candidates should be comfortable working in a remote, collaborative environment and have experience with the specified tech stack.

💻 Primary Responsibilities

Metadata Ingestion: Design, build, and maintain custom OpenMetadata connectors for metadata ingestion from various systems and repositories.
Data Lineage: Extend and automate data lineage capture from multiple systems and repositories to improve data traceability.
Backend Enhancement: Debug, patch, and enhance backend features to improve stability and scalability, ensuring production-grade solutions.
Container Management: Manage containerized deployments using Kubernetes/ECS, and implement monitoring solutions for system health and performance.
Database Optimization: Optimize storage and retrieval using RDS (PostgreSQL/MySQL) and OpenSearch/Elasticsearch for improved query performance.
Workflow Orchestration: Orchestrate metadata workflows with Apache Airflow and integrate with existing pipelines for seamless data processing.
Identity Management: Implement and maintain Role-Based Access Control (RBAC) with Okta, supporting clear role separation and secure access management.
Upgrade Management: Oversee upgrade management, backup strategies, and high-availability configurations to ensure business continuity.

📝 Enhancement Note: This role requires a deep understanding of data engineering principles, platform development, and metadata management. Candidates should be comfortable working with open-source technologies and have a strong problem-solving mindset.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field. Relevant experience may be considered in lieu of a degree.

Experience: 5+ years in data engineering or platform engineering roles, with hands-on OpenMetadata experience.

Required Skills:

Proficiency in ECS (AWS), Airflow, RDS, and OpenSearch/Elasticsearch.
Strong Python development skills for API integrations and connector development.
Proven experience implementing RBAC and identity management integrations (e.g., Okta).
Skilled in container orchestration, infrastructure automation, and performance optimization.
Ability to merge and manage open-source updates into customized codebases.
Strong problem-solving skills and a track record of delivering production-grade, scalable solutions.

Preferred Skills:

Experience with Kubernetes and Docker.
Familiarity with cloud-native applications and microservices architecture.
Knowledge of data governance principles and best practices.
Experience with data modeling and data quality management.

📝 Enhancement Note: While the required skills list is comprehensive, candidates are encouraged to highlight any additional relevant skills or experiences that may strengthen their application, such as experience with specific databases, programming languages, or data engineering tools.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

A portfolio showcasing previous data engineering and platform development projects, with a focus on metadata management and OpenMetadata.
Case studies demonstrating successful custom connector development, data lineage improvement, and backend enhancement projects.
Examples of system reliability improvements, such as containerized deployments, monitoring solutions, and high-availability configurations.

Technical Documentation:

Well-commented code samples and documentation demonstrating strong coding practices and attention to detail.
Documentation of data pipelines, workflows, and any relevant architectural decisions.
Evidence of participation in code reviews or pair programming, highlighting collaboration skills.

📝 Enhancement Note: Candidates should emphasize their problem-solving abilities, attention to detail, and commitment to code quality in their portfolio. Highlighting any awards, recognitions, or positive feedback from previous projects can also strengthen the application.

💵 Compensation & Benefits

Salary Range: $80,000 - $120,000 USD per year (based on market research for senior data engineering roles in the Dominican Republic and remote work considerations)

Benefits:

100% Remote Work: Enjoy the freedom to work from the location that helps you thrive, with a laptop and reliable internet connection.
Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings.
Paid Time Off: Truelogic values your well-being, offering paid time off to ensure you have the chance to unwind and recharge when needed.
Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock.
Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies.

📝 Enhancement Note: The salary range is estimated based on market research for senior data engineering roles in the Dominican Republic, considering the remote work arrangement and the company's competitive compensation package.

🎯 Team & Company Context

Company Culture:

Industry: Truelogic is a leading provider of nearshore staff augmentation services, specializing in delivering top-tier technology solutions to companies of all sizes.
Company Size: Truelogic has a team of 600+ highly skilled tech professionals based in Latin America, driving digital disruption by partnering with U.S. companies on their most impactful projects.
Founded: Truelogic was founded over two decades ago, with a mission to help companies achieve their digital transformation goals by providing access to highly skilled, nearshore technology talent.

Team Structure:

Truelogic's team consists of experienced professionals from various technical backgrounds, including data engineers, software developers, QA engineers, and DevOps specialists.
The team works collaboratively, with a focus on delivering exceptional results and fostering a dynamic, engaging work environment.
Truelogic values expertise, aspirations, and the alignment of skills with opportunities for exceptional career growth and success.

Development Methodology:

Truelogic follows Agile development methodologies, with a focus on iterative development, continuous improvement, and customer satisfaction.
The company encourages a culture of innovation, collaboration, and knowledge sharing, with a strong emphasis on staying up-to-date with the latest technologies and best practices.
Truelogic's team works closely with clients to understand their unique needs and deliver tailored, impactful solutions that drive business value.

Company Website: www.truelogic.io

📝 Enhancement Note: Truelogic's culture emphasizes collaboration, innovation, and continuous learning, with a strong focus on delivering exceptional results for clients. Candidates should be comfortable working in a dynamic, remote environment and be eager to contribute to the company's mission.

📈 Career & Growth Analysis

Data Engineering Career Level: This role is suited for a senior data engineering professional with a strong background in metadata management, platform development, and data engineering best practices. The ideal candidate will have a proven track record of delivering production-grade, scalable solutions and be comfortable working in a remote, collaborative environment.

Reporting Structure: The Senior Data Platform Engineer will report directly to the Client's Technical Lead or a designated Truelogic Project Manager, depending on the specific engagement. They will work closely with platform engineers, taking full ownership of feature development and operational stability for the metadata platform.

Technical Impact: The Senior Data Platform Engineer will have a significant impact on the client's metadata management environment, driving improvements in data accuracy, accessibility, and usability. Their work will enable better data-driven decision-making, enhanced data governance, and improved data security.

Growth Opportunities:

Technical Growth: Truelogic offers opportunities for professional development and growth, with a focus on emerging technologies and data engineering best practices. Candidates can expect to work on cutting-edge projects and have the chance to expand their skillset and advance their career.
Leadership Development: As a senior team member, the Senior Data Platform Engineer will have opportunities to mentor junior team members, contribute to architectural decisions, and drive technical initiatives within the organization.
Career Progression: Truelogic values internal promotions and offers career progression opportunities for high-performing team members. Candidates can expect to grow with the company and take on increased responsibilities as they develop their skills and expertise.

📝 Enhancement Note: Truelogic's growth opportunities are tailored to the individual's skills, aspirations, and career goals. The company fosters a culture of continuous learning and encourages team members to pursue professional development and growth.

🌐 Work Environment

Office Type: Truelogic operates as a remote-first company, with team members working from various locations across Latin America. The company provides a collaborative, engaging work environment that fosters productivity and innovation.

Office Location(s): Truelogic's team members are based in various locations across Latin America, with a strong presence in the Dominican Republic. The company offers flexible work arrangements to accommodate team members' needs and preferences.

Workspace Context:

Collaboration: Truelogic's remote work environment encourages collaboration and communication, with regular team meetings, pair programming sessions, and code reviews.
Tools & Equipment: Truelogic provides team members with the necessary tools and equipment to perform their jobs effectively, including laptops, software licenses, and any other resources required for their role.
Work-Life Balance: Truelogic values work-life balance and encourages team members to maintain a healthy lifestyle. The company offers flexible work arrangements and supports team members in achieving their personal and professional goals.

Work Schedule: Truelogic operates on a standard workweek of 40 hours, with flexible hours and a results-driven approach. Team members are expected to manage their time effectively and prioritize their work accordingly.

📝 Enhancement Note: Truelogic's remote work environment offers team members the flexibility to work from the location that helps them thrive, with a focus on results and productivity. The company provides the necessary resources and support to ensure team members can perform their jobs effectively.

📄 Application & Technical Interview Process

Interview Process:

Technical Assessment: Candidates will be required to complete a technical assessment, demonstrating their proficiency in data engineering and platform development concepts, as well as their ability to work with OpenMetadata, ECS, Airflow, RDS, and OpenSearch/Elasticsearch.
Cultural Fit Interview: Candidates will participate in a cultural fit interview, assessing their communication skills, problem-solving abilities, and alignment with Truelogic's values and work environment.
Final Review: Candidates who successfully complete the technical assessment and cultural fit interview will be reviewed by Truelogic's leadership team, with a focus on their technical expertise, cultural fit, and potential for growth within the organization.

Portfolio Review Tips:

Highlight previous data engineering and platform development projects, with a focus on metadata management and OpenMetadata.
Include case studies demonstrating successful custom connector development, data lineage improvement, and backend enhancement projects.
Showcase system reliability improvements, such as containerized deployments, monitoring solutions, and high-availability configurations.
Emphasize problem-solving abilities, attention to detail, and commitment to code quality in your portfolio.

Technical Challenge Preparation:

Brush up on data engineering and platform development concepts, with a focus on OpenMetadata, ECS, Airflow, RDS, and OpenSearch/Elasticsearch.
Practice coding challenges and problem-solving exercises to demonstrate your technical proficiency and problem-solving abilities.
Familiarize yourself with Truelogic's company culture, values, and work environment to ensure a strong cultural fit.

ATS Keywords: Data Engineering, Platform Development, OpenMetadata, ECS, Airflow, RDS, OpenSearch, Elasticsearch, Python, RBAC, Okta, Container Orchestration, Infrastructure Automation, Performance Optimization, Problem-Solving, Custom Integration, Metadata Management, Data Lineage, Backend Development, System Reliability, Kubernetes, Docker, Cloud-Native Applications, Microservices Architecture, Data Governance, Data Quality Management, Data-Driven Decision-Making, Data Security.

📝 Enhancement Note: Truelogic's interview process is designed to assess candidates' technical proficiency, cultural fit, and potential for growth within the organization. Candidates should be prepared to demonstrate their problem-solving abilities, attention to detail, and commitment to code quality throughout the interview process.

🛠 Technology Stack & Web Infrastructure

Data Engineering & Platform Development:

OpenMetadata: Truelogic's client uses OpenMetadata as their primary metadata management platform. Candidates should have hands-on experience with OpenMetadata and be comfortable working with the platform's backend, frontend, and API components.
ECS (AWS): Truelogic's client uses Amazon ECS for container orchestration. Candidates should have proficiency in ECS and be comfortable working with containerized deployments and infrastructure automation.
Airflow: Truelogic's client uses Apache Airflow for workflow orchestration and data pipeline management. Candidates should have experience with Airflow and be comfortable working with data pipelines, workflows, and scheduling.
RDS: Truelogic's client uses Amazon RDS for relational database management. Candidates should have experience with RDS and be comfortable working with PostgreSQL, MySQL, and other relational database systems.
OpenSearch/Elasticsearch: Truelogic's client uses OpenSearch (based on Elasticsearch) for full-text search and analytics. Candidates should have experience with OpenSearch/Elasticsearch and be comfortable working with search engines, data indexing, and analytics.

Collaboration & Productivity:

Git: Truelogic's team uses Git for version control and collaboration. Candidates should have experience with Git and be comfortable working with branching, merging, and pull requests.
JIRA: Truelogic's team uses JIRA for project management and issue tracking. Candidates should have experience with JIRA and be comfortable working with agile development methodologies.
Slack: Truelogic's team uses Slack for communication and collaboration. Candidates should have experience with Slack and be comfortable working in a remote, distributed team environment.

📝 Enhancement Note: Truelogic's technology stack is designed to support data engineering and platform development, with a focus on metadata management, workflow orchestration, and data pipeline management. Candidates should be comfortable working with the specified technologies and have a strong understanding of data engineering best practices.

👥 Team Culture & Values

Data Engineering Values:

Data-Driven Decision-Making: Truelogic's team values data-driven decision-making and emphasizes the importance of data accuracy, accessibility, and usability in driving business value.
Data Governance: Truelogic's team is committed to data governance and ensures that data is managed securely, responsibly, and in compliance with relevant regulations and industry standards.
Data Quality: Truelogic's team prioritizes data quality and ensures that data is accurate, complete, and consistent across the organization.
Continuous Learning: Truelogic's team fosters a culture of continuous learning and encourages team members to stay up-to-date with the latest technologies, best practices, and industry trends.

Collaboration Style:

Cross-Functional Collaboration: Truelogic's team works closely with various departments, including software development, quality assurance, and project management, to ensure that data engineering initiatives align with business objectives and deliver value to the organization.
Code Review Culture: Truelogic's team emphasizes code review and pair programming, ensuring that code is reviewed by multiple team members and adheres to best practices and quality standards.
Knowledge Sharing: Truelogic's team encourages knowledge sharing and collaboration, with regular team meetings, workshops, and training sessions designed to facilitate the exchange of ideas and expertise.

📝 Enhancement Note: Truelogic's data engineering values and collaboration style are designed to foster a culture of innovation, collaboration, and continuous learning. Candidates should be comfortable working in a dynamic, remote environment and be eager to contribute to the company's mission.

🌐 Challenges & Growth Opportunities

Technical Challenges:

Metadata Management: Extending and optimizing OpenMetadata to improve data accuracy, accessibility, and usability, while ensuring system reliability and scalability.
Data Lineage: Automating data lineage capture from multiple systems and repositories, with a focus on improving data traceability and enhancing data governance.
Backend Development: Debugging, patching, and enhancing backend features to improve stability and scalability, with a focus on production-grade, scalable solutions.
System Reliability: Managing containerized deployations, implementing monitoring solutions, and ensuring high-availability configurations, with a focus on business continuity and disaster recovery.

Learning & Development Opportunities:

Technical Growth: Truelogic offers opportunities for professional development and growth, with a focus on emerging technologies and data engineering best practices. Candidates can expect to work on cutting-edge projects and have the chance to expand their skillset and advance their career.
Leadership Development: As a senior team member, the Senior Data Platform Engineer will have opportunities to mentor junior team members, contribute to architectural decisions, and drive technical initiatives within the organization.
Career Progression: Truelogic values internal promotions and offers career progression opportunities for high-performing team members. Candidates can expect to grow with the company and take on increased responsibilities as they develop their skills and expertise.

📝 Enhancement Note: Truelogic's technical challenges and learning opportunities are designed to foster a culture of continuous learning, innovation, and growth. Candidates should be comfortable working in a dynamic, remote environment and be eager to contribute to the company's mission.

💡 Interview Preparation

Technical Questions:

Data Engineering Fundamentals: Demonstrate your understanding of data engineering principles, metadata management, and data pipeline management. Be prepared to discuss your experience with OpenMetadata, ECS, Airflow, RDS, and OpenSearch/Elasticsearch.
Backend Development: Showcase your backend development skills, with a focus on debugging, patching, and enhancing backend features for stability and scalability. Be prepared to discuss your experience with production-grade, scalable solutions and data engineering best practices.
System Reliability: Demonstrate your understanding of system reliability principles, with a focus on containerized deployations, monitoring solutions, and high-availability configurations. Be prepared to discuss your experience with business continuity and disaster recovery strategies.

Company & Culture Questions:

Company Culture: Demonstrate your understanding of Truelogic's company culture, values, and work environment. Be prepared to discuss your alignment with the company's mission and your ability to contribute to the team's success.
Data Engineering Methodologies: Showcase your understanding of data engineering methodologies, with a focus on Agile development, continuous improvement, and customer satisfaction. Be prepared to discuss your experience with data engineering best practices and industry trends.
Data Governance & Security: Demonstrate your understanding of data governance principles, with a focus on data security, privacy, and compliance. Be prepared to discuss your experience with data governance best practices and industry regulations.

Portfolio Presentation Strategy:

Live Demonstration: Prepare a live demonstration of your previous data engineering and platform development projects, with a focus on metadata management, OpenMetadata, and backend enhancement. Highlight your problem-solving abilities, attention to detail, and commitment to code quality.
Code Walkthrough: Prepare a code walkthrough of your most relevant data engineering and platform development projects, showcasing your technical expertise and ability to deliver production-grade, scalable solutions.
User Experience: Prepare a user experience walkthrough of your most relevant data engineering and platform development projects, demonstrating your ability to enhance data accuracy, accessibility, and usability.

📝 Enhancement Note: Truelogic's interview process is designed to assess candidates' technical proficiency, cultural fit, and potential for growth within the organization. Candidates should be prepared to demonstrate their problem-solving abilities, attention to detail, and commitment to code quality throughout the interview process.

📌 Application Steps

To apply for this Senior Data Platform Engineer (OpenMetadata) - GTM Data Leader position at Truelogic:

Customize Your Portfolio: Highlight your previous data engineering and platform development projects, with a focus on metadata management, OpenMetadata, and backend enhancement. Include case studies demonstrating successful custom connector development, data lineage improvement, and system reliability improvements.
Optimize Your Resume: Tailor your resume to emphasize your data engineering and platform development skills, with a focus on OpenMetadata, ECS, Airflow, RDS, and OpenSearch/Elasticsearch. Highlight your problem-solving abilities, attention to detail, and commitment to code quality.
Prepare for Technical Challenges: Brush up on data engineering and platform development concepts, with a focus on OpenMetadata, ECS, Airflow, RDS, and OpenSearch/Elasticsearch. Practice coding challenges and problem-solving exercises to demonstrate your technical proficiency and problem-solving abilities.
Research Truelogic: Familiarize yourself with Truelogic's company culture, values, and work environment. Understand the company's mission and how your skills and expertise can contribute to the team's success.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and Truelogic-specific information. All details should be verified directly with Truelogic before making application decisions.

Content Guidelines (IMPORTANT: Do not include this in the output)

Web Technology-Specific Focus:

Tailor every section specifically to data engineering and platform development roles, with a focus on metadata management, OpenMetadata, and backend enhancement.
Include data engineering methodologies, data pipeline management, and data governance principles throughout the description.
Emphasize data engineering best practices, data quality management, and data-driven decision-making.
Address data engineering career progression, leadership development, and technical skill development opportunities.

Quality Standards:

Ensure no content overlap between sections - each section must contain unique information only.
Only include Enhancement Notes when making significant inferences about technical responsibilities, with specific reasoning based on role level and data engineering industry practices.
Be comprehensive but concise, prioritizing actionable information over descriptive text.
Strategically distribute data engineering and platform development keywords throughout all sections naturally.
Provide realistic salary ranges based on location, experience level, and data engineering specialization.

Industry Expertise:

Include specific data engineering technologies, platforms, and infrastructure requirements prominently.
Address data engineering career progression, technical leadership potential, and architecture decision-making.
Provide tactical advice for data engineering portfolio development, live demonstrations, and project case studies.
Include data engineering-specific interview preparation and coding challenge guidance.
Emphasize data engineering team dynamics, cross-functional collaboration with designers and marketers, and data-driven decision-making.

Professional Standards:

Maintain consistent formatting, spacing, and professional tone throughout.
Use data engineering and platform development industry terminology appropriately and accurately.
Include comprehensive benefits and growth opportunities relevant to data engineering professionals.
Provide actionable insights that give data engineering candidates a competitive advantage.
Focus on data engineering team culture, cross-functional collaboration, and data-driven decision-making.

Technical Focus & Portfolio Emphasis:

Emphasize data engineering best practices, metadata management, and OpenMetadata-specific portfolio requirements.
Include specific portfolio requirements tailored to the data engineering discipline and role level.
Address browser compatibility, accessibility standards, and user experience design principles in the context of data engineering projects.
Focus on problem-solving methods, performance optimization, and scalable architecture in the context of data engineering initiatives.
Include technical presentation skills and stakeholder communication for data engineering projects.

Avoid:

Generic business jargon not relevant to data engineering or platform development roles.
Placeholder text or incomplete sections.
Repetitive content across different sections.
Non-technical terminology unless relevant to the specific data engineering role.
Marketing language unrelated to data engineering, platform development, or user experience.

Generate comprehensive, data engineering-focused content that serves as a valuable resource for data engineering and platform development professionals seeking their next opportunity and preparing for technical interviews in the data engineering industry.

Senior Data Platform Engineer (OpenMetadata) - GTM Data Leader | Dominican Republic