Summary
✨ AI‑Generated
A senior data engineering position focused on building modern data platforms, developing reliable pipelines, improving data quality, and supporting analytics through cloud-based technologies and strong engineering practices.
Highlights
Hybrid working arrangement with opportunities to design scalable data platforms, build robust pipelines, and collaborate across technical teams.
Description
Senior Data Engineer – London, UK, 2 days a week in client office, 3 days remote,
Open for Permanent, Contract(Inside IR 35/Outside IR 35), FTC
Mandatory Skillsets: Python, Snowflake, dBT, dremio, glue jobs, Apache iceberg, AWS ,SQL
Key Responsibilities:
• Architect and Develop: Contribute to the platform’s architectural design and build integration, modelling, data persistence, and analytical systems.
• Data Pipelines: Implement, maintain, and test robust data pipelines.
• Metadata Management: Develop and manage metadata processes and tools.
• Performance Monitoring: Ensure the stability and performance of data pipelines.
• Data Quality: Implement tools for data curation, metadata management, and quality assurance.
• Collaboration: Engage with business and technology teams to align the platform with organizational goals.
Preferred Technical Skills:
• Programming: 5+ years of experience in Python/Java.
• Cloud Expertise: Strong understanding of AWS services (e.g., Lambda, Step Functions, ECS).
• Data Platforms: Hands-on experience with Snowflake and data stack technologies like Apache Iceberg and Spark.
• Workflow Orchestration: Exposure to tools like Apache Airflow, Prefect, Dagster, or DBT.
• Data Services: Familiarity with AWS Glue, Lake Formation, EMR, EventBridge, Athena, and similar services.
• Metadata Tools: Experience with tools like Amundsen, Atlas, DataHub, OpenDataDiscovery, or Marquez.
• RDBMS: Knowledge of PostgreSQL is a plus.
• Industry Experience: Proven experience building enterprise-wide data and analytics systems, preferably in financial services or asset management.
