Experience: 10+ years in Data Engineering, with at least 2+ years in a formal leadership or management role.
Data Platform Mastery: Proven experience with modern data platforms such as Snowflake (AI Data Cloud) and cloud-native services. Good understanding of open-source table formats, specifically Apache Iceberg.
Programming: Expert-level proficiency in Java, Python, and SQL.
Big Data & Orchestration: Hands-on experience with Spark, Kafka, and orchestration tools like Apache Airflow, Dagster, or dbt.
Data Modeling: Deep understanding of data warehousing and modern data lakehouse architecture.
Nice to Haves:
Mentorship: Proven track record of upskilling junior and senior engineers.
Communication: Ability to explain complex technical concepts to non-technical stakeholders in the wealth management business.
Problem Solving: A "builder" mindset with the ability to navigate ambiguity in a fast-paced environment.
What You'll Be Doing:
Team Leadership: Lead and mentor a local team of data engineers in Birmingham.
Platform Ownership: Design, build, and maintain robust data platforms and pipelines.
AI Readiness: Implement strategies to make data "AI-ready."
Technical Governance: Set and enforce high standards for code quality and testing.
Stakeholder Management: Collaborate with Data Scientists, Product Managers, and Application teams.
Local Advocacy: Act as the technical face of the team in the Birmingham office.
Perks and Benefits:
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.