Fractal Analytics
Senior Data Engineer
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Senior Data Engineer
West London
Onsite 2 – 3 days per week
Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets. An ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.
Please visit Fractal | Intelligence for Imagination for more information about Fractal
We are seeking a skilled and detail-oriented Senior Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. You will be responsible for transforming raw data into reliable, high-quality datasets that fuel analytics, reporting, and machine learning initiatives. The ideal candidate is passionate about data quality, automation, and solving complex data challenges in a collaborative environment.
Key Responsibilities:
- Design & Build Pipelines: Develop, deploy, and monitor robust, scalable, and efficient ETL/ELT data pipelines using modern tools and frameworks.
- Data Modeling & Architecture: Design, implement, and optimize data models (relational, dimensional, NoSQL) in data warehouses, data lakes, or lakehouses.
- Data Integration: Ingest, process, and integrate data from diverse sources (Kafka, pub-sub, databases, APIs, streaming platforms, SaaS applications, flat files).
- Data Quality & Governance: Implement data validation, cleansing, and monitoring processes to ensure accuracy, consistency, and reliability of data assets.
- Infrastructure & Optimization: Manage and optimize cloud data infrastructure (e.g., GCP, AWS, Azure) and on-premise systems for performance, cost-efficiency, and scalability.
- Collaboration: Partner closely with Data Analysts, Data Scientists, and business stakeholders to understand data requirements and deliver solutions that meet their needs.
- Automation & CI/CD: Automate data pipeline deployments, testing, and monitoring using CI/CD principles and tools.
- Documentation: Maintain clear and comprehensive documentation for data pipelines, models, and processes.
- Troubleshooting: Investigate and resolve data pipeline failures, performance bottlenecks, and data quality issues.
- On-call Support: This role requires to be available for out-of-office on-call support on a rotation.
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Required Qualifications:
- Experience: 7+ years of professional experience in data engineering or a related role across GCP services
- SQL: Strong expertise in writing complex, optimized SQL queries for data extraction and transformation.
- ETL/ELT: Hands-on experience building data pipelines using frameworks like Apache Spark, Apache Airflow, DBT, Fivetran, Matillion, or equivalent.
- Databases: Solid understanding of relational databases (e.g., PostgreSQL, MySQL) and experience with modern data warehousing solutions (e.g., Snowflake, BigQuery, Redshift, Synapse).
- Data Modeling: Knowledge of data modeling principles (e.g., star schema, snowflake schema, normalization).
- Programming: Proficiency in Python and/or Scala for data processing and pipeline development.
- Agentic workflows: Experience using agentic workflows in day-to-day deliveries
- Version Control: Experience with Git and collaborative development workflows.
- Problem-Solving: Strong analytical and problem-solving skills with a focus on data quality and system reliability.
- Communication: Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.
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