Description

Design and implement advanced data and analytics architectures using AWS and Databricks, owning the full lifecycle from data modeling to high-availability delivery.

This role is on-site.

Responsibilities

• Build and maintain ETL and data engineering solutions, managing large-scale data warehouses and lakes.
• Implement data modeling using star schemas, derivatives, and measures.
• Own data quality, lineage tracking, and data discoverability across the platform.
• Collaborate with business owners to translate data requirements into technical specifications within an Agile environment.

Required Skills

• 5+ years of experience in advanced data and analytics architecture or data engineering.
• 3+ years of coding experience with Python.
• Expert-level SQL skills, including writing and optimizing complex queries.
• Hands-on experience with PySpark, Spark SQL, and Spark Streaming.
• Proficiency with AWS Data & Analytics services: Athena, Glue, DynamoDB, Redshift, Kinesis, and Lambda.
• Experience with the Databricks Lakehouse platform.
• Practical knowledge of NoSQL databases.
• Experience with the full software development life cycle, including code reviews, source control, and testing.

Preferred Skills

• Bachelor's or Master's degree in Computer Science, IT, or a relevant field.

Key Skills

Education

ANY GRADUATE