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Metro locations, generalist Senior Data Engineer title, and hybrid working increase competition.
Core data engineering skills transfer across industries, though fintech/governance experience moderately raises fit sensitivity.
Multiple mandatory technical requirements (Python, SQL, cloud, orchestration, containers, CI/CD) increase screening strictness.
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Build and maintain data pipelines and tooling for data ingestion and modelling across the organisation.
Develop and enforce data and coding standards with robust testing and documentation aligned to data governance.
Identify and implement process improvements to automate, optimize, and scale data delivery and processing.
Work Experience Required: Previous experience as a data engineer in a start-up or fast-paced organisation.
Strong Python programming skills with production-grade tooling, test-driven approach, and well-documented code.
Proficient in SQL and experienced with cloud application deployment (GCP, AWS, Azure preferred).
Experience with orchestration tools (Airflow, Dagster, or Prefect), container technology (Docker, Kubernetes), and CI/CD pipelines (preferably Azure DevOps).
Experienced in data modelling and building scalable data engineering solutions in a fast-paced environment.
Has strong operational execution skills evidenced by managing development lifecycle from prototyping to productionising.
Comfortable working across multiple teams (Finance, Operations, Credit Risk, Product, Management) to enable data-driven decision making.