Cloud Data Engineer
- Design and build scalable ETL/ELT pipelines on AWS using Databricks, Spark, Python, and SQL.
- Integrate AWS services (S3, Redshift, Glue, Lambda, EMR, DMS) for ingestion, transformation, storage, and orchestration.
- Develop and optimize Databricks workflows and Spark jobs for batch and streaming processing.
- Ensure data quality, governance, and security through validation, monitoring, and access controls.
- Collaborate with analysts, data scientists, and stakeholders to translate requirements into technical solutions.
- Tune and troubleshoot SQL/Spark performance and mentor junior engineers on best practices.
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
- Active Public Trust Clearance.
- Ability to travel 0-25%, on average, based on the work you do and the clients and industries/sectors you serve.
- 5+ years of AWS S3 experience
- Minimum 5 years of hands-on experience in data engineering or related roles; previous leadership or mentorship experience a strong plus.
- 5+ years of experience with AWS (must be comfortable with S3, DMS, Glue etc).
- 5+ years of experience with Databricks & Spark:
- 2+ years of experience with Python for data processing and workflow automation.
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