Senior Business Intelligence Data Engineer
Role details
Job location
Tech stack
Job description
The Senior Business Intelligence Data Engineer will own the full life cycle of understanding the business requirements data and designing the migration of our data from several systems to a cutting-edge Databricks environment, architecting, implementing, and optimizing ETL/ELT processes to ensure robust, secure, and analytics-ready data flows for our business operations.
A successful Senior Business Intelligence Data Engineer demonstrates customer focus, a drive for results, and ease with ambiguous data requests and definitions; influences change, naturally accepts ownership for project deliverables, explores opportunities to add value to job responsibilities, and continues to develop critical skills and technical expertise. Projects will span across all time horizons, from early in Vehicle development process through end of production and often require integration of data across multiple functions, including Engineering, Program Management, Planning, Forecasting, Sales, and Manufacturing.
What You'll Do
- Collaborate with stakeholders, including data analysts, data scientists, architects, and business teams, to ensure data solutions meet organizational requirements and compliance standards.
- Design, develop, and maintain data pipelines to transfer data from various databases to Databricks, leveraging both batch and real-time methodologies as appropriate.
- Lead the overall ETL/ELT architecture, including extraction, transformation, and data loading strategies, ensuring scalability, performance, and data integrity. Optimize and tune ETL/ELT processes for large-scale and real-time data movement, ensuring resource efficiency. Ensure data security, quality, and compliance across the whole process.
- Model, integrate, and optimize data structures in the Databricks platform, taking into account data lakes, data warehousing needs, and analytics workloads.
- Automate and monitor data workflows for reliability, transparency, and fault tolerance throughout the migration and beyond. Document data flows, transformation logic, and technical specifications for all data integration processes, enabling maintainability and smooth knowledge transfer., This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.
Requirements
- Bachelor's Degree in Computer Science, Data Analytics, Engineering, Operations Management or related field
- 5+ years of experience in data engineering or related roles, with demonstrated expertise in database migrations and ETL/ELT process design.
- Deep hands-on experience with databases Oracle, SQL Server, MySQL, Teradata, Snowflake
- In-depth knowledge of Databricks (including PySpark, Databricks SQL, and Lakehouse architectures).
- Expertise in ETL/ELT tools and frameworks (e.g., Informatica, Talend, Databricks Workflows, or custom pipelines).
- Proven ability to design and implement scalable, efficient data pipelines and to optimize complex transformations in modern cloud environments.
- Demonstrated experience in data modeling and integration for analytics and BI use cases.
- Excellent communication and documentation skills for cross-functional collaboration and process transparency.
What Will Give You a Competitive Edge (Preferred Qualifications)
- Master's degree in Computer Science, Software Engineering, or related field
- Knowledge of data governance, metadata management, or data quality/observability
- Familiarity with schema design and data contracts
- Experience handling various file formats (video, audio, image)
- Experience with Databricks, Snowflake, or similar platforms
- Experience designing and implementing robust data ingestion frameworks for heterogeneous data sources (structured/unstructured files, external suppliers, supplier chain systems)