Senior ML Data Engineer working on data pipeline curation for Mobileye's autonomous vehicle dataset. Collaborating across teams to enhance ML engineering and vision model applications.
About the role
- Lead Cloud Data Engineer managing data pipelines and implementations on cloud platforms in Financial Services. Collaborating for enhanced data architecture and team mentorship.
Responsibilities
- Design, develop, and optimize end‑to‑end data pipelines using Databricks
- Implement and manage Lakehouse architecture with Delta tables
- Develop high‑performance PySpark and SQL transformations
- Ensure data quality, integrity, and performance across pipelines
- Lead troubleshooting, root cause analysis, and performance tuning
- Collaborate with Architects, Business Analysts, and downstream consumers
- Support CI/CD implementation for Databricks jobs and notebooks
- Mentor junior engineers and review code for quality and best practices
- Ensure adherence to security, governance, and compliance standards
Requirements
- 10-14 years of hands on experience with AWS Cloud Data Engineering with Databricks platform
- Expertise in Data Modeling and DB design
- Hands on experience in setting up data pipelines for ETL jobs across multiple data sources.
- Hands‑on experience with performance tuning, Git, Jenkins, and enterprise job scheduling tools (Autosys / Airflow)
- Basic understanding of Data warehousing and ETL concepts
- Knowledge of CI/CD tools (GitHub, Azure DevOps)
- Advanced SQL and Python skills
- Experience working in Agile delivery environments
Benefits
- inclusive development opportunities
- flexible work-life support
- paid volunteer days
- vibrant employee networks
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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