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Data Engineer

Fractal
City of London
4 days ago
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Overview

Data Engineer role at Fractal in West London. Onsite 2 – 3 days per week. Fractal is a strategic AI partner to Fortune 500 companies, with a mission to power human decision in the enterprise. The company emphasizes imagination and intelligence to empower decision-making.

We are seeking a skilled and detail-oriented Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. You will transform 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 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.
Required Qualifications
  • Experience: 5+ years of professional experience in data engineering or a related role across GCP services.
  • Programming: Proficiency in Python and/or Scala for data processing and pipeline development.
  • 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).
  • 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.
Details
  • Seniority level: Mid-Senior level
  • Employment type: Full-time
  • Job function: Information Technology
  • Industries: Business Consulting and Services


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