Senior Data Engineer

Role & responsibilities

5+ years of experience in data engineering, data architecture, data platforms & analytics

At least 3+ years of experience with Databricks, PySpark, Python, and SQL.

Consulting / customer-facing experience, working with external clients across a variety of industry markets

Comfortable writing code in both Python and SQL

Proficiency in SQL and experience with data warehousing solutions

Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one

Strong understanding of data modeling, ETL processes, and data architecture principles.

Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals

Familiarity with CI/CD for production deployments - GitHub, Azure DevOps, Azure Pipelines

Working knowledge of MLOps methodologies

Design and deployment of performant end-to-end data architectures

Experience with technical project delivery - managing scope and timelines Documentation and white-boarding skills

Experience working with clients and managing conflicts

Build skills in technical areas that support the deployment and integration of Databricks-based solutions to complete customer projects

Good to have Databricks Certifications