oracle
Lead Data Engineer
008523-JPMS-GLOBAL MERGERS & ACQUI
London, GBR
Full-time
Senior · 8+ years experience
Onsite
Discovered 2 weeks ago
PythonPySparkdbtSQLAirflowTerraform
Free
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Role Overview
As a Lead Data Engineer at JPMorgan Chase within Personal Investing, you will design, build, and operate a robust cloud-native data platform and pipelines that power analytics, regulatory reporting, and data-promoten applications. You will help us deliver reliable, scalable, observable, and secure data solutions by applying strong software engineering fundamentals and modern data engineering patterns. You’ll work closely with partners across product, analytics, and engineering to translate business needs into resilient technical designs. You’ll also contribute to engineering excellence through best practices, mentoring, and thoughtful technical direction.
Key Skills for This Role
PythonPySparkdbtSQLAirflowTerraform
Full Job Posting
Job summary
As a Lead Data Engineer at JPMorgan Chase within Personal Investing, you will design, build, and operate a robust cloud-native data platform and pipelines that power analytics, regulatory reporting, and data-promoten applications. You will help us deliver reliable, scalable, observable, and secure data solutions by applying strong software engineering fundamentals and modern data engineering patterns. You’ll work closely with partners across product, analytics, and engineering to translate business needs into resilient technical designs. You’ll also contribute to engineering excellence through best practices, mentoring, and thoughtful technical direction.
Job responsibilities
- Design scalable, reusable data processing and data quality frameworks using Python, PySpark, and dbt
- Build and optimize batch and streaming data pipelines with strong performance, fault tolerance, and observability
- Develop and operate workflow orchestration (e.g., Apache Airflow) to schedule, monitor, and manage data movement and transformations
- Model and transform data for analytics using SQL and dbt to support business intelligence and reporting workloads
- Write production-grade Python/PySpark code with disciplined testing, performance tuning, and maintainable object-oriented design
- Implement infrastructure-as-code (e.g., Terraform) to provision and manage cloud-based data platform components
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