Data Engineer

The Lead Data Engineer is responsible for architecting and delivering scalable, high-performance data pipelines and platforms across cloud environments. This role leads the adoption of modern data architectures such as a Lakehouse and Databricks, strengthens data integration and governance, supports analytics and AI/ML use cases, and mentors data engineers and analysts to advance engineering standards and team capability.

Required Skills, Knowledge, And Experience

• 7–10 years of implementation experience in cloud data architecture, with at least 5 years in AWS environments.
• Proficiency in AWS services: Glue, Redshift, Athena, Lake Formation, SageMaker, Bedrock, Step Functions.
• Extensive experience working with Databricks.
• Working knowledge of the Alation data governance tool.
• Strong skills in SQL (T-SQL), Python (PySpark/Pandas), DAX, Power Query (M), PL/SQL.
• Experience with databases: SQL Server, Oracle, PostgreSQL, Azure SQL, Teradata.
• Skilled in Power BI, Git, Visual Studio Code, SSMS.
• Knowledge of architectural patterns: Medallion architecture, data mesh, Lakehouse, SOA data layers.
• Excellent communication, collaboration, and leadership abilities.

Preferred Skills, Knowledge, And Experience

• AWS and Databricks certifications.
• Experience leading cloud migration and data modernization initiatives.
• Designing and implementing scalable data architectures in AWS and Databricks.
• Managing data governance, security, and compliance in complex environments.
• Mentoring junior architects and engineers.
• Working with cross-functional teams to deliver business value through data.

Required Education

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field

Preferred Education

• Masters Degree