Data Engineer
Posted 2
views
Summary
Builds and maintains data pipelines, data models, schemas, and warehouses (Azure/Databricks-class cloud platforms) so the Data & Analytics team and business units can access reliable, secure data. Day-to-day work spans SQL, Python/PySpark, ETL/ELT orchestration, data quality checks, and documentation.
Build and maintain reliable data pipelines and platforms that help the Data & Analytics team and business units easily access, organize, and use data for analytics and reporting.
Key Responsibilities
- Build, maintain, and optimize data pipelines for data ingestion and transformation.
- Develop and maintain data models, schemas, and data warehouses.
- Maintain data dictionaries and technical documentation.
- Monitor and troubleshoot data pipelines to ensure reliability and performance.
- Implement data quality and validation checks.
- Work with Data Scientists, Data Analysts, IT, and business teams to deliver data solutions.
- Ensure data is accessible, secure, and usable across the platform.
Minimum Qualifications
Education
- Bachelor's degree in Computer Science, IT, Information Systems, Engineering, Mathematics, Statistics, or a related field.
Technical Skills
- Proficient in SQL and Python; PySpark is preferred.
- Experience with Azure, Databricks, or similar cloud data platforms.
- Experience with ETL/ELT pipelines and data orchestration tools.
- Knowledge of data modeling, data warehousing, and medallion/layered architecture.
- Exposure to data governance and data quality is a plus.
Core Competencies
- Strong problem-solving and analytical skills.
- Adaptable to new technologies and tools.
- Able to work effectively with cross-functional teams.
- Strong attention to data quality and technical detail.
- Good communication and stakeholder management skills.