Solutions Engineer, Data Cloud at Jungle Scout

📍 Job Overview

Job Title: Solutions Engineer, Data Cloud
Company: Jungle Scout
Location: Remote - Canada, Vancouver, BC
Job Type: Full-Time
Category: Web Technology - DevOps, Data Engineer
Date Posted: 2025-06-17
Experience Level: Mid-Level (2-5 years)
Remote Status: Remote (Canada)

🚀 Role Summary

Collaborate with cross-functional teams to understand customer needs and develop data solutions.
Present technical solutions to non-technical stakeholders and manage customer timelines.
Build, QA, and deliver custom datasets and reports using SQL, Python, and modern data stacks.
Troubleshoot data anomalies and improve data pipelines for enhanced customer experience.

💻 Primary Responsibilities

Customer Interaction & Solution Development:
- Support Product, Customer Success, and Professional Services teams on customer calls to understand core needs and develop solution specifications.
- Present technical solutions to non-technical stakeholders and manage customer timelines.
Data Solution Delivery:
- Build data solutions from provided specifications using SQL, Python, and modern data stacks.
- QA custom datasets and reports to ensure accuracy and performance.
- Collaborate with engineering and data teams to resolve issues and improve data pipelines.
Sales Enablement & Customer Onboarding:
- Create queries, reports, and internal dashboards to illustrate the value of Jungle Scout's data for sales enablement.
- Support the creation of onboarding guides, FAQs, queries, and other materials to accelerate customer enablement.
Team Collaboration & Communication:
- Connect with the team through scrum meetings and Slack updates.
- Collaborate with engineering and data teams to create delivery pipelines for custom data (bonus).

🎓 Skills & Qualifications

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

Experience: 3+ years of experience working directly with customers to implement or integrate data solutions. Extensive hands-on experience with data integration, analysis, and building pipelines.

Required Skills:

Expertise in SQL for data analysis
Experience with Python for data analysis and automation
Experience building and troubleshooting ETL and data pipelines
Experience working with Data Lakes (S3/Glue preferred)
Experience with modern data warehouses like Snowflake, Redshift, BigQuery
Experience with reporting infrastructure (Tableau, PowerBI, Looker, etc.)
Experience with common data integration patterns and systems (FTP, S3, Snowflake, GCP Filestore, Azure Blog Storage)
Experience with a BI Tool (Tableau, Looker, PowerBI, etc.)

Preferred Skills:

Experience in Ecommerce

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate experience in data integration, analysis, and building pipelines using SQL and Python.
Showcase projects that involve working with modern data stacks, including data lakes, cloud warehouses, and BI tools.
Highlight customer-facing data projects that required presenting technical solutions to non-technical stakeholders.

Technical Documentation:

Provide examples of solution specifications, data pipeline documentation, and customer-facing materials (onboarding guides, FAQs, queries).
Include code snippets and explanations for complex data analysis and integration tasks.

💵 Compensation & Benefits

Salary Range: CAD 85,000 - 110,000 per year (based on Canadian market standards for mid-level data engineering roles)

Benefits:

Competitive compensation packages with performance bonus and equity
Comprehensive health benefits and retirement program
Flexible time off, including Volunteer Time Off (VTO)
Paid parental leave policy with ramp-back period
Growth culture with opportunities for skill elevation and training
Ability to make a significant impact on customer experience and business success

🎯 Team & Company Context

Company Culture:

Jungle Scout values a remote-first, customer-centric, and collaborative work environment.
The team thrives in a fast-paced, innovative environment, pushing the boundaries of data and technology.
Jungle Scout prioritizes diversity, equity, and inclusion, hiring intentionally to create an inclusive environment.

Team Structure:

The Solutions Engineer will work closely with Product, Customer Success, Professional Services, Engineering, and Data teams.
The role will involve cross-functional collaboration and reporting to the Data team.

Development Methodology:

Jungle Scout follows an Agile development methodology, with a focus on customer needs and continuous improvement.
The team uses scrum meetings and Slack updates for communication and project management.

Company Website: Jungle Scout

📝 Enhancement Note: Jungle Scout's remote-first culture allows for flexible work arrangements and encourages work-life balance. The company's focus on customer-centric innovation fosters a dynamic and engaging work environment.

📈 Career & Growth Analysis

Web Technology Career Level: Mid-Level Solutions Engineer, focusing on data integration, analysis, and customer-facing data solutions.

Reporting Structure: The Solutions Engineer will report to the Data team and collaborate with various cross-functional teams, including Product, Customer Success, and Professional Services.

Technical Impact: The Solutions Engineer will have a significant impact on customer experience by developing and delivering tailored data solutions. They will also contribute to improving data pipelines and enhancing Jungle Scout's data offerings.

Growth Opportunities:

Technical Skill Development: Expand expertise in modern data stacks, emerging technologies, and advanced data analysis techniques.
Team Leadership: Develop leadership skills by managing customer timelines, supporting onboarding processes, and mentoring junior team members.
Architecture Decision-Making: Contribute to strategic decisions regarding data architecture, pipeline optimization, and data warehouse management.

📝 Enhancement Note: Jungle Scout's growth culture and focus on continuous improvement provide ample opportunities for mid-level Solutions Engineers to advance their careers. The company's commitment to employee development and skill elevation ensures that team members have the resources and support needed to grow professionally.

🌐 Work Environment

Office Type: Remote-first with hub offices in Chicago, IL, and Austin, TX. Team members can choose to work from home, at a hub office, or from a co-working space.

Office Location(s): Vancouver, BC, Canada (primary remote location)

Workspace Context:

Remote Workspace: Jungle Scout provides resources and support for remote team members to create a productive and comfortable home office environment.
Hub Offices: Jungle Scout's hub offices offer collaborative workspaces with access to meeting rooms, event spaces, and amenities.
Team Interaction: Jungle Scout fosters a collaborative and inclusive work environment, with regular team-building activities and virtual events.

Work Schedule: Flexible work hours with a focus on results and customer impact. Jungle Scout offers a competitive benefits package, including comprehensive health benefits, retirement program, and flexible time off.

📝 Enhancement Note: Jungle Scout's remote-first culture and flexible work arrangements allow team members to balance work and personal responsibilities effectively. The company's commitment to employee well-being and work-life balance ensures that team members have the support they need to thrive in their roles.

📄 Application & Technical Interview Process

Interview Process:

Resume Screening: Review of resume and portfolio materials to assess relevant experience and skills.
Phone Screen: A brief phone call to discuss the role, team, and company culture.
Technical Assessment: A hands-on assessment involving data analysis, pipeline building, and customer-facing scenario simulations.
Final Interview: A conversation with hiring managers and team members to evaluate cultural fit and career aspirations.

Portfolio Review Tips:

Highlight projects that demonstrate experience in data integration, analysis, and customer-facing data solutions.
Include examples of solution specifications, data pipeline documentation, and customer-facing materials.
Showcase technical skills and problem-solving abilities through code snippets and explanations.

Technical Challenge Preparation:

Brush up on SQL and Python skills, focusing on data analysis, integration, and pipeline building.
Familiarize yourself with modern data stacks, including data lakes, cloud warehouses, and BI tools.
Practice presenting technical solutions to non-technical stakeholders and managing customer timelines.

ATS Keywords: SQL, Python, Data Integration, Data Analysis, ETL, Data Pipeline, Data Lake, Cloud Warehouse, BI Tool, Reporting Infrastructure, Customer-Facing, Problem-Solving, Technical Communication, Data Architecture, Data Warehouse, Data Pipeline Optimization, Data Solution Delivery, Customer Success, Professional Services, Agile, Scrum, Remote Work, Flexible Hours, Work-Life Balance, Employee Development, Skill Elevation, Team Collaboration, Cross-Functional Teams, Data-Driven Decision Making, Customer-Centric Innovation, Data Solution Development, Data Solution Delivery, Data Pipeline Optimization, Data Warehouse Management, Data Architecture, Technical Leadership, Technical Skill Development, Team Leadership, Architecture Decision-Making.

📝 Enhancement Note: Jungle Scout's technical interview process focuses on assessing candidates' problem-solving skills, technical expertise, and cultural fit. By preparing thoroughly and showcasing relevant experience, candidates can demonstrate their potential to excel in the Solutions Engineer role.

🛠 Technology Stack & Web Infrastructure

Data Technologies:

Data Lakes: S3, Glue
Cloud Warehouses: Snowflake, Redshift, BigQuery
BI Tools: Tableau, PowerBI, Looker
Programming Languages: SQL, Python
Data Integration Patterns & Systems: FTP, S3, Snowflake, GCP Filestore, Azure Blog Storage

Data Pipeline Tools:

ETL Tools: Talend, Pentaho, AWS Glue
Data Quality Tools: Great Expectations, Trifacta
Data Governance Tools: Apache Atlas, AWS Lake Formation

Collaboration & Project Management Tools:

Project Management: Jira, Asana, Trello
Communication: Slack, Microsoft Teams
Documentation: Confluence, Notion, Google Drive

📝 Enhancement Note: Jungle Scout's modern data stack enables team members to work with cutting-edge technologies and tools. The company's commitment to staying current with industry trends ensures that team members have the resources and support needed to develop their skills and advance their careers.

👥 Team Culture & Values

Web Development Values:

Customer-Centric: Focus on understanding customer needs and delivering tailored data solutions.
Innovative: Embrace continuous improvement and push the boundaries of data and technology.
Collaborative: Work closely with cross-functional teams to develop and deliver data solutions.
Data-Driven: Make informed decisions based on data analysis and insights.
Quality-Oriented: Hold a high bar for data accuracy, performance, and customer experience.

Collaboration Style:

Cross-Functional Integration: Collaborate with Product, Customer Success, Professional Services, Engineering, and Data teams to develop and deliver data solutions.
Code Review Culture: Encourage peer-to-peer learning and knowledge sharing through code reviews and pair programming.
Knowledge Sharing: Foster a culture of continuous learning and skill development through workshops, training, and mentoring programs.

📝 Enhancement Note: Jungle Scout's customer-centric and collaborative culture fosters a dynamic and engaging work environment. The company's commitment to continuous improvement and data-driven decision-making ensures that team members have the support they need to excel in their roles and advance their careers.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Data Complexity: Work with large, complex datasets and develop efficient data solutions to meet customer needs.
Data Silos: Break down data silos and integrate data from various sources to provide a comprehensive view of customer information.
Data Governance: Ensure data accuracy, security, and compliance with relevant regulations and industry standards.
Data Pipeline Optimization: Continuously improve data pipelines to enhance performance, scalability, and reliability.
Emerging Technologies: Stay current with emerging data technologies and tools to drive innovation and competitive advantage.

Learning & Development Opportunities:

Technical Skill Development: Expand expertise in modern data stacks, emerging technologies, and advanced data analysis techniques.
Leadership Development: Develop leadership skills by managing customer timelines, supporting onboarding processes, and mentoring junior team members.
Architecture Decision-Making: Contribute to strategic decisions regarding data architecture, pipeline optimization, and data warehouse management.

📝 Enhancement Note: Jungle Scout's dynamic and innovative environment presents unique challenges and growth opportunities for mid-level Solutions Engineers. The company's commitment to employee development and skill elevation ensures that team members have the resources and support needed to overcome technical challenges and advance their careers.

💡 Interview Preparation

Technical Questions:

Data Analysis: Explain your approach to data analysis and provide examples of complex data problems you've solved using SQL and Python.
Data Integration: Describe your experience with data integration, including working with various data sources, formats, and tools.
Data Pipeline Building: Walk through your process for building and maintaining data pipelines, including troubleshooting and optimization techniques.
Customer-Facing Data Solutions: Discuss your experience presenting technical solutions to non-technical stakeholders and managing customer timelines.

Company & Culture Questions:

Company Culture: Explain what aspects of Jungle Scout's culture appeal to you and how you would contribute to the team's success.
Customer-Centric Innovation: Describe your approach to understanding customer needs and developing data solutions that drive business value.
Data-Driven Decision Making: Share an example of a data-driven decision you've made in a previous role and the impact it had on customer experience or business success.

Portfolio Presentation Strategy:

Data Solution Demonstration: Present a customer-facing data solution you've developed, highlighting the problem it solves, the data integration and analysis techniques used, and the impact it had on the customer.
Data Pipeline Walkthrough: Provide a step-by-step walkthrough of a data pipeline you've built, including the tools and technologies used, the challenges faced, and the solutions implemented.
Customer Success Story: Share a success story from a previous role, focusing on how you used data to improve customer experience and drive business growth.

📝 Enhancement Note: Jungle Scout's interview process focuses on assessing candidates' problem-solving skills, technical expertise, and cultural fit. By preparing thoroughly and showcasing relevant experience, candidates can demonstrate their potential to excel in the Solutions Engineer role and contribute to the company's continued success.

📌 Application Steps

To apply for this Solutions Engineer, Data Cloud position at Jungle Scout:

Submit your application through the application link provided.
Customize your resume and portfolio to highlight relevant experience and skills, focusing on data integration, analysis, and customer-facing data solutions.
Prepare for the technical assessment by brushing up on SQL, Python, and modern data stack technologies.
Research Jungle Scout's company culture, values, and mission to ensure a strong fit with your personal and professional goals.
Practice presenting technical solutions to non-technical stakeholders and managing customer timelines to demonstrate your customer-facing skills.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web technology industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Solutions Engineer, Data Cloud