Key Skills: Pyspark, People Management, Databricks, SQL, Python, Data Engineer, Data quality, AWS, ETL
Roles and Responsibilities:
- Lead and manage data engineering teams, balancing technical delivery with people leadership and execution.
- Own data quality practices across pipelines, including profiling, validation, and remediation workflows.
- Develop and optimize data processing using Python and PySpark on Databricks.
- Write and maintain advanced SQL queries across multiple databases to support analytics and data products.
- Ensure data pipelines follow ETL/ELT standards and support downstream analytics ecosystems.
Skills Required:
- 11 - 13 years of experience in data management, data analysis, data profiling, and statistical techniques; including 5 years managing data engineering teams
- Strong experience in Python and PySpark.
- Hands-on experience with Databricks.
- Strong knowledge of SQL and complex query development.
- Experience in Data Engineering and ETL/ELT.
- Strong understanding of Data Quality, Data Profiling, and Data Validation.
- Experience managing and mentoring data engineering teams.
- Good understanding of data pipelines and analytics data platforms.
- Strong problem-solving, communication, and stakeholder management skills.
Valuable to Have
- Experience with AWS cloud services.
- Knowledge of data governance and data management practices.
- Experience with statistical and data analysis techniques.