Data Engineering - Python Glue

We are looking for a Data Engineering Lead with deep expertise in AWS, Python, and modern data engineering practices to architect and deliver scalable, secure, and efficient data solutions. In this role, you’ll lead the design and development of ETL pipelines, implement robust data warehousing solutions, and support machine learning workflows across various business domains.

Your strong understanding of ETL and Data Warehousing concepts, including Slowly Changing Dimensions (SCD) and Medallion Architecture, along with proficiency in SQL and AWS-native tools, will be key to success.

Key Responsibilities

Data Pipeline & Architecture

• Design, develop, and maintain scalable ETL pipelines leveraging AWS services such as Glue, S3, Lambda, and Athena.
• Hands on Python and Pyspark coding experience.
• Implement Medallion Architecture (bronze, silver, gold layers) to organize and optimize data for both operational and analytical use cases.
• Apply best practices in data modeling and data warehousing, including handling SCD Type 1 and Type 2 transformations.

Must-Have Qualifications

• 5+ years of hands-on experience in data engineering, particularly with Python, PySpark, and SQL.
• Proven experience building ETL pipelines using AWS services (Glue, Lambda, S3, Athena, Step Functions).
• Strong knowledge of Data Warehousing concepts, SCD Types (Type 1, Type 2), and Medallion Architecture.
• Solid understanding of data modeling, partitioning, and performance optimization in big data environments.
• Excellent communication skills with the ability to explain technical topics to non-technical stakeholders.

Job Types: Full-time, Permanent

Benefits:

• Health insurance

Work Location: In person