Cloud Data Analytics Platform Engineer

📍 Job Overview

Job Title: Cloud Data Analytics Platform Engineer - VP
Company: Citi
Location: London, United Kingdom
Job Type: Hybrid (2 days working at home per week)
Category: Cloud & Infrastructure
Date Posted: 2025-07-31
Experience Level: 5-10 years
Remote Status: On-site with hybrid option

🚀 Role Summary

Design and build a robust, multi-cloud data analytics platform using AWS, GCP, and other emerging cloud environments.
Manage data lakes and data zones, ensuring data quality, discoverability, and accessibility.
Implement and maintain enterprise-grade data governance capabilities.
Champion Infrastructure as Code (IaC) using Terraform and other tools like Harness, Tekton, or Lightspeed.
Collaborate with data engineering, information security, and platform teams to define and enforce best practices.
Manage and optimize Kubernetes clusters for running critical data processing workloads using Spark and Airflow.
Implement and maintain robust cloud security measures, including cloud networking, IAM, encryption, data isolation, and secure service communication.
Leverage experience with Snowflake and Databricks to enhance the data platform's capabilities and performance.
Contribute to the development of event-driven data pipelines using Kafka and schema registries.
Apply FinOps principles and multi-cloud cost optimization techniques to ensure efficient resource utilization and cost control.

💻 Primary Responsibilities

Architect and Build: Design and implement a robust, cloud-native data analytics platform spanning AWS, GCP, and other emerging cloud environments. Leverage services like S3/GCS, Glue, BigQuery, Pub/Sub, SQS/SNS, MWAA/Composer, and more to create a seamless data experience. 📝 Enhancement Note: This role requires a deep understanding of cloud data analytics services and a strong architectural mindset.
Data Lake, Data Zone, Data Governance: Design, build, and manage data lakes and data zones within our cloud environment, ensuring data quality, discoverability, and accessibility for various downstream consumers. Implement and maintain enterprise-grade data governance capabilities, integrating with data catalogs and lineage tracking tools to ensure data quality, security, and compliance. 📝 Enhancement Note: This role demands a solid grasp of data governance principles and experience with relevant tools and frameworks.
Infrastructure as Code (IaC): Champion IaC using Terraform and preferably other tools like Harness, Tekton, or Lightspeed, developing modular patterns and establishing CI/CD pipelines to automate infrastructure management and ensure consistency across our environments. 📝 Enhancement Note: Proficiency in Terraform and other IaC tools is essential for this role, as is experience with CI/CD pipelines.
Collaboration and Best Practices: Work closely with data engineering, information security, and platform teams to define and enforce best practices for data infrastructure, fostering a culture of collaboration and knowledge sharing. 📝 Enhancement Note: Strong communication and collaboration skills are crucial for success in this role.
Kubernetes and Orchestration: Manage and optimize Kubernetes clusters, specifically for running critical data processing workloads using Spark and Airflow. 📝 Enhancement Note: A deep understanding of Kubernetes and experience with Spark and Airflow are required for this role.
Cloud Security: Implement and maintain robust security measures, including cloud networking, IAM, encryption, data isolation, and secure service communication (VPC peering, PrivateLink, PSC/PSA). 📝 Enhancement Note: A firm grasp of cloud security principles and best practices is essential for this role.
Snowflake and Databricks (Optional, but highly desired): Leverage your experience with Snowflake and Databricks to enhance our data platform's capabilities and performance. While not mandatory, experience with these technologies is a significant advantage. 📝 Enhancement Note: Experience with Snowflake and Databricks can provide a competitive edge in this role.
Event-Driven Architectures, FinOps and Cost Optimization (Optional): Contribute to the development of event-driven data pipelines using Kafka and schema registries, enabling real-time data insights and responsiveness. Apply FinOps principles and multi-cloud cost optimization techniques to ensure efficient resource utilization and cost control. 📝 Enhancement Note: Experience with event-driven architectures, Kafka, and FinOps principles can provide a significant advantage in this role.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field. 📝 Enhancement Note: A relevant master's degree can provide a competitive advantage.

Experience: 8-13 years of relevant experience in Data Engineering & Infrastructure Automation. 📝 Enhancement Note: Candidates with more than 10 years of experience may be considered for a senior role.

Required Skills:

Hands-on experience with AWS and/or GCP, including a deep understanding of their data analytics service offerings.
Proven experience designing, building, and managing data lakes and data zones.
Solid experience with Terraform and preferably other tools like Harness, Tekton, or Lightspeed for CI/CD pipeline management.
Strong command of Kubernetes, especially in the context of data processing workloads.
A firm grasp of cloud security principles and best practices.
Experience working in financial services, banking, or on data-related cloud transformation projects within the financial industry. (Highly Desired)

Preferred Skills:

Experience with Snowflake and Databricks.
Familiarity with event-driven architectures, Kafka, and FinOps principles.
Knowledge of compliance frameworks relevant to cloud data.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Cloud Data Analytics Platform: A well-documented project showcasing your experience designing and implementing a cloud-native data analytics platform across multiple cloud environments.
Data Lake & Governance: A project demonstrating your ability to manage data lakes and implement data governance capabilities, ensuring data quality, discoverability, and accessibility.
Infrastructure as Code: A project highlighting your proficiency in IaC using Terraform and other tools, with a focus on modular patterns and CI/CD pipelines.
Kubernetes & Orchestration: A project showcasing your experience managing and optimizing Kubernetes clusters for data processing workloads using Spark and Airflow.

Technical Documentation:

Code Quality: Documented code with clear comments and adherence to best practices.
Version Control: Experience with Git or other version control systems, with a focus on collaborative development and code reviews.
Deployment Processes: Detailed documentation of deployment processes, including CI/CD pipelines, infrastructure as code, and server configuration.
Testing Methodologies: Experience with testing methodologies, performance metrics, and optimization techniques relevant to cloud data analytics platforms.

💵 Compensation & Benefits

Salary Range: £120,000 - £160,000 per year, depending on experience and qualifications. 📝 Enhancement Note: This estimate is based on market research for similar roles in London and adjusted for the candidate's experience level.

Benefits:

27 days annual leave (plus bank holidays)
Discretional annual performance-related bonus
Private Medical Care & Life Insurance
Employee Assistance Program
Pension Plan
Paid Parental Leave
Special discounts for employees, family, and friends
Access to an array of learning and development resources

🎯 Team & Company Context

Company Culture: Citi is a global financial services company with a strong focus on innovation, collaboration, and customer-centricity. 📝 Enhancement Note: Citi's culture values diversity, inclusion, and work-life balance, with a hybrid working model that allows for up to 2 days working at home per week.

Industry: Financial Services 📝 Enhancement Note: This role is ideal for candidates with experience in the financial services industry or a strong interest in working in this dynamic and challenging sector.

Company Size: Large (over 200,000 employees) 📝 Enhancement Note: Working at Citi offers opportunities for career growth and development within a large, global organization.

Founded: 1812 📝 Enhancement Note: Citi's long history and established presence in the financial services industry provide a stable and secure work environment.

Team Structure:

Web Technology Team: A diverse team of cloud data analytics engineers, data engineers, and data architects working collaboratively to design, build, and maintain Citi's data analytics platform.
Reporting Structure: This role reports directly to the Head of Cloud Data Analytics Platform Engineering, with a matrix reporting structure to other teams, including data engineering, information security, and platform teams.
Cross-Functional Collaboration: Close collaboration with designers, marketers, and business teams to ensure data insights drive informed decision-making and enhance the customer experience.

Development Methodology:

Agile/Scrum: Citi uses Agile methodologies for software development, with sprint planning, daily stand-ups, and regular retrospectives.
Code Review: Citi emphasizes code reviews to ensure code quality, knowledge sharing, and collaborative development.
CI/CD Pipelines: Citi leverages CI/CD pipelines to automate deployment, testing, and release management for its cloud data analytics platform.

Company Website: Citi

📝 Enhancement Note: Citi's global presence and diverse business lines offer unique opportunities for career growth and development within the financial services industry.

📈 Career & Growth Analysis

Web Technology Career Level: This role is at the senior level, requiring a deep understanding of cloud data analytics, data governance, and infrastructure automation. 📝 Enhancement Note: Candidates with more than 10 years of experience may be considered for a senior role or a leadership position within the team.

Reporting Structure: This role reports directly to the Head of Cloud Data Analytics Platform Engineering, with a matrix reporting structure to other teams, including data engineering, information security, and platform teams. 📝 Enhancement Note: This reporting structure fosters collaboration and knowledge sharing across teams and promotes career growth opportunities.

Technical Impact: This role has a significant impact on Citi's data analytics capabilities, driving data-driven decision-making and enhancing the customer experience. 📝 Enhancement Note: The successful candidate will have a strong influence on Citi's data strategy and architecture.

Growth Opportunities:

Technical Leadership: This role offers opportunities for technical leadership, with the potential to mentor junior team members, define best practices, and drive architectural decisions.
Career Progression: Citi's large and diverse organization provides ample opportunities for career progression, with potential roles in data architecture, data engineering management, or other senior leadership positions.
Emerging Technologies: Citi's commitment to innovation and emerging technologies offers opportunities to work with cutting-edge cloud data analytics tools and platforms.

📝 Enhancement Note: Citi's culture of collaboration, knowledge sharing, and continuous learning provides an ideal environment for career growth and development.

🌐 Work Environment

Office Type: Hybrid (2 days working at home per week) 📝 Enhancement Note: Citi's hybrid working model offers flexibility and work-life balance, with the opportunity to work from home up to two days per week.

Office Location(s): London, United Kingdom 📝 Enhancement Note: London is a global financial hub, offering a dynamic and multicultural work environment.

Workspace Context:

Collaborative Workspace: Citi's offices feature collaborative workspaces designed to foster teamwork and knowledge sharing.
Development Tools: Citi provides access to the latest development tools, multiple monitors, and testing devices to ensure optimal productivity.
Cross-Functional Collaboration: Citi's offices encourage cross-functional collaboration, with dedicated spaces for team meetings, workshops, and training sessions.

Work Schedule: Citi's work schedule is typically 9:00 AM to 5:30 PM, with flexibility for deployment windows, maintenance, and project deadlines. 📝 Enhancement Note: Citi's flexible work schedule accommodates the needs of its global workforce and promotes work-life balance.

📝 Enhancement Note: Citi's work environment is designed to support the well-being and productivity of its employees, with a focus on collaboration, innovation, and continuous learning.

📄 Application & Technical Interview Process

Interview Process:

Technical Assessment: A hands-on technical assessment focused on cloud data analytics, data governance, and infrastructure automation, with a strong emphasis on problem-solving and architectural design.
Behavioral Interview: An in-depth behavioral interview to assess the candidate's cultural fit, communication skills, and leadership potential.
Final Evaluation: A final evaluation based on the candidate's technical skills, cultural fit, and alignment with Citi's values and mission.

Portfolio Review Tips:

Cloud Data Analytics Platform: Highlight your experience designing and implementing cloud-native data analytics platforms, with a focus on data quality, security, and performance.
Data Lake & Governance: Demonstrate your ability to manage data lakes and implement data governance capabilities, ensuring data quality, discoverability, and accessibility.
Infrastructure as Code: Showcase your proficiency in IaC using Terraform and other tools, with a focus on modular patterns and CI/CD pipelines.
Kubernetes & Orchestration: Highlight your experience managing and optimizing Kubernetes clusters for data processing workloads using Spark and Airflow.

Technical Challenge Preparation:

Cloud Data Analytics: Brush up on your knowledge of cloud data analytics services, with a focus on AWS, GCP, and other emerging cloud environments.
Data Governance: Familiarize yourself with data governance principles, tools, and best practices relevant to cloud data analytics.
Infrastructure Automation: Review your experience with IaC, CI/CD pipelines, and server configuration, with a focus on Terraform and other relevant tools.

Company & Culture Questions: Research Citi's history, mission, and values, and be prepared to discuss how your skills and experience align with the company's goals and culture. 📝 Enhancement Note: Citi's commitment to innovation, collaboration, and customer-centricity provides ample opportunities for candidates to demonstrate their fit with the company's culture.

ATS Keywords: (See the comprehensive list of web development and server administration-relevant keywords for resume optimization, organized by category: programming languages, web frameworks, server technologies, databases, tools, methodologies, soft skills, industry terms)

📝 Enhancement Note: Tailor your resume and portfolio to highlight the relevant ATS keywords for this role, ensuring your application stands out in Citi's applicant tracking system.

🛠 Technology Stack & Web Infrastructure

Cloud Data Analytics Platform:

AWS: Amazon S3, Glue, BigQuery, Pub/Sub, SQS/SNS, MWAA/Composer
GCP: Google Cloud Storage, BigQuery, Pub/Sub, Cloud Functions, Cloud Composer
Emerging Cloud Environments: Azure, Oracle Cloud, IBM Cloud, Alibaba Cloud, Tencent Cloud

Data Governance Tools:

Data Catalogs: Apache Atlas, AWS Glue Data Catalog, Google Cloud Data Catalog
Data Lineage Tracking: Apache Atlas, AWS Glue Data Lineage, Google Cloud Data Lineage
Data Quality: Talend, Informatica, AWS Glue Data Quality, Google Cloud Data Quality

Infrastructure as Code (IaC) Tools:

Terraform: Terraform Enterprise, Terraform Cloud
Harness: Harness Continuous Delivery, Harness Enterprise
Tekton: Tekton Pipelines, Tekton Triggers
Lightspeed: Lightspeed Enterprise, Lightspeed Cloud

Kubernetes & Orchestration:

Kubernetes: Kubernetes v1.21+, with experience in running critical data processing workloads using Spark and Airflow.
Spark: Apache Spark 3.1+, with experience in data processing, machine learning, and graph processing.
Airflow: Apache Airflow 2.2+, with experience in workflow orchestration, data pipeline management, and dynamic pipeline generation.

📝 Enhancement Note: Familiarize yourself with Citi's technology stack and be prepared to discuss your experience with relevant tools and platforms during the interview process.

👥 Team Culture & Values

Web Development Values:

Innovation: Citi values innovation and encourages its employees to think creatively and challenge the status quo.
Collaboration: Citi fosters a culture of collaboration, with a strong emphasis on teamwork, knowledge sharing, and collective problem-solving.
Customer-Centricity: Citi is committed to delivering exceptional customer experiences and values employees who prioritize customer needs and exceed expectations.
Integrity: Citi upholds the highest ethical standards and expects its employees to act with honesty, transparency, and accountability.

Collaboration Style:

Cross-Functional Integration: Citi encourages close collaboration between developers, designers, and stakeholders to ensure data insights drive informed decision-making and enhance the customer experience.
Code Review Culture: Citi emphasizes code reviews to ensure code quality, knowledge sharing, and collaborative development.
Knowledge Sharing: Citi values knowledge sharing and encourages employees to mentor and learn from one another to drive continuous learning and improvement.

📝 Enhancement Note: Citi's culture values diversity, inclusion, and work-life balance, with a hybrid working model that allows for up to 2 days working at home per week.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Cloud Data Analytics: Stay up-to-date with the latest cloud data analytics services, tools, and best practices, with a focus on AWS, GCP, and other emerging cloud environments.
Data Governance: Keep up-to-date with data governance principles, tools, and best practices relevant to cloud data analytics, with a focus on data quality, security, and compliance.
Infrastructure Automation: Continuously improve your skills in IaC, CI/CD pipelines, and server configuration, with a focus on Terraform and other relevant tools.
Kubernetes & Orchestration: Deepen your understanding of Kubernetes, with a focus on running critical data processing workloads using Spark and Airflow, and stay current with the latest Kubernetes releases and best practices.

Learning & Development Opportunities:

Cloud Data Analytics: Pursue relevant certifications, attend industry conferences, and engage in online communities to stay current with the latest cloud data analytics trends and best practices.
Data Governance: Participate in data governance workshops, webinars, and online courses to enhance your knowledge of data governance principles, tools, and best practices.
Infrastructure Automation: Contribute to open-source projects, engage in online forums, and attend industry events to expand your skills in IaC, CI/CD pipelines, and server configuration.
Kubernetes & Orchestration: Join Kubernetes user groups, participate in online forums, and attend Kubernetes conferences to stay current with the latest Kubernetes releases, best practices, and emerging use cases.

📝 Enhancement Note: Citi's commitment to innovation, collaboration, and continuous learning provides an ideal environment for technical growth and development.

💡 Interview Preparation

Technical Questions:

Cloud Data Analytics: Be prepared to discuss your experience with cloud data analytics services, with a focus on AWS, GCP, and other emerging cloud environments.
Data Governance: Demonstrate your understanding of data governance principles, tools, and best practices relevant to cloud data analytics.
Infrastructure Automation: Showcase your proficiency in IaC, CI/CD pipelines, and server configuration, with a focus on Terraform and other relevant tools.
Kubernetes & Orchestration: Highlight your experience managing and optimizing Kubernetes clusters for data processing workloads using Spark and Airflow.

Company & Culture Questions:

Citi's History and Mission: Research Citi's history, mission, and values, and be prepared to discuss how your skills and experience align with the company's goals and culture.
Citi's Technology Stack: Familiarize yourself with Citi's technology stack and be prepared to discuss your experience with relevant tools and platforms.
Citi's Work Environment: Understand Citi's hybrid working model and be prepared to discuss how you can thrive in this work environment.

Portfolio Presentation Strategy:

Cloud Data Analytics Platform: Highlight your experience designing and implementing cloud-native data analytics platforms, with a focus on data quality, security, and performance.
Data Lake & Governance: Demonstrate your ability to manage data lakes and implement data governance capabilities, ensuring data quality, discoverability, and accessibility.
Infrastructure as Code: Showcase your proficiency in IaC using Terraform and other tools, with a focus on modular patterns and CI/CD pipelines.
Kubernetes & Orchestration: Highlight your experience managing and optimizing Kubernetes clusters for data processing workloads using Spark and Airflow.

📝 Enhancement Note: Tailor your interview preparation strategy to highlight your unique skills, experiences, and cultural fit with Citi's values and mission.

📌 Application Steps

To apply for this Cloud Data Analytics Platform Engineer - VP role at Citi:

Tailor Your Resume: Highlight your relevant experience with cloud data analytics, data governance, and infrastructure automation, with a focus on AWS, GCP, and other emerging cloud environments. Include specific examples of your experience with Terraform, Kubernetes, and Spark/Airflow.
Customize Your Portfolio: Showcase your experience designing and implementing cloud-native data analytics platforms, with a focus on data quality, security, and performance. Include specific examples of your work with data lakes, data governance, and infrastructure as code.
Prepare for Technical Assessments: Brush up on your knowledge of cloud data analytics services, data governance principles, and infrastructure automation tools. Practice coding challenges and prepare for architectural design assessments.
Research Citi: Familiarize yourself with Citi's history, mission, values, and technology stack. Prepare thoughtful questions to ask during your interviews, demonstrating your interest in the company and the role.
Apply: Submit your application through the Citi careers portal, following the instructions provided.

📝 Enhancement Note: Tailor your application materials to highlight your unique skills, experiences, and cultural fit with Citi's values and mission, and follow the application steps outlined above to maximize your chances of success.

Cloud Data Analytics Platform Engineer - VP