AWS Data Engineer

Title: AWS Data Engineer Location: McLean, VA (Hybrid) Duration: 12 months Video Interview Job description: Responsibilities: • Design, build, and maintain scalable data pipelines using AWS Glue and Databricks. • Develop and optimize ETL/ELT processes using PySpark and Python. • Collaborate with data scientists, analysts, and stakeholders to enable efficient data access and transformation. • Implement and maintain data lake and warehouse solutions on AWS (S3, Glue Catalog, Redshift, Athena, etc.). • Ensure data quality, consistency, and reliability across systems. • Optimize performance of large-scale distributed data processing workflows. • Develop automation scripts and frameworks for data ingestion, transformation, and validation. • Follow best practices for data governance, security, and compliance. Required Skills & Experience: • 5–8 years of hands-on experience in Data Engineering. • Strong proficiency in Python and PySpark for data processing and transformation. • Expertise in AWS services — particularly Glue, S3, Lambda, Redshift, and Athena. • Hands-on experience with Databricks for building and managing data pipelines. • Experience working with large-scale data systems and optimizing performance. • Solid understanding of data modeling, data lake architecture, and ETL design principles. • Strong problem-solving skills and ability to work independently in a fast-paced environment. “Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”