Job Overview As a Lead / Principal Databricks Data Engineer, you'll shape and deliver scalable data platforms that turn complex information into trusted, useful insights. You'll lead data engineering design and implementation across public cloud environments, guide technical decisions, and partner with analytics and business intelligence teams. Your work will connect data sources, strengthen data management integration, and support reliable analytics and model training. Responsibilities Lead data engineering and software development for big data systems, including Databricks and Spark solutions. Design and maintain ETL (extract, transform, load) pipelines, data warehouses, cloud databases, and SQL databases using SQL and Python. Define data model design, data modeling, dimensional modeling, database design, and data warehousing design standards. Manage query performance and data quality across AWS, Azure Data Lake, Microsoft SQL Server, Oracle, Apache Hive, and Hadoop environments. Collaborate with teams using Looker and other business intelligence tools; integrate RESTful APIs and linked data.

Your impact:

Reliable, well-modeled data helps analytics teams deliver clearer insights for business decisions. Qualifications Demonstrated data engineering experience with big data, Spark, ETL pipeline development, SQL, and Python. Strong analysis skills and experience with data management integration, query management, and data warehouse platforms. Familiarity with AWS, Azure Data Lake, public cloud, Microsoft SQL Server, Oracle, SQL databases, cloud databases, Hadoop, and Apache Hive. Experience with Agile delivery; Java, Informatica, Talend, Bash (Unix shell), and shell scripting are useful. Exposure to Looker, analytics, business intelligence tools, linked data, RESTful APIs, and model training is preferred.

Pay:

$50.00 - $55.00 per hour Expected hours: 40.0 per week

Work Location:

In person