Python Data Engineer Cloud

Brains Workgroup•Iselin, NJ

4d•Hybrid

About The Position

Our client, a major bank in Central New Jersey, is seeking a hands-on Cloud Data Engineer with strong Python, SQL, and ETL skills. The role is hybrid, with one or two days per week onsite, and is a 12-month contract with possible extensions or an option to hire. Compensation is $80–$85 per hour on W-2, depending on experience; C2C may also be possible. The Cloud Data Engineer designs, builds, and maintains scalable data pipelines and Azure cloud platforms. The role works with large datasets, optimizes data workflows, and ensures secure, efficient data storage and processing in cloud environments. Responsibilities include developing Spark programs in Databricks, working with Delta Lake and data warehouses, implementing data integration and dimensional modeling, and processing structured, semi-structured, and unstructured data. The engineer also monitors and troubleshoots Databricks jobs, applies data management, security, and governance best practices, and contributes to enterprise data warehouse solutions and cloud data platform migrations.

Requirements

At least 5 years of Python coding experience.
At least 5 years of SQL Server-based development involving large datasets.
At least 5 years of experience developing and deploying ETL pipelines using Databricks PySpark.
Experience with a cloud data warehouse such as Synapse, BigQuery, Redshift, or Snowflake.
Data warehousing experience, including OLTP, OLAP, dimensions, facts, and data modeling.
Experience leading an enterprise-wide Cloud Data Platform migration, with strong architectural and design skills.
Experience with cloud-based data architectures, messaging, and analytics.
Cloud certification(s).

Nice To Haves

Experience with Airflow.

Responsibilities

Build and optimize data pipelines for ingestion, transformation, and loading from various sources while ensuring data quality and integrity.
Design, develop, and deploy Spark programs in Databricks to process and analyze large volumes of data.
Work with Delta Lake, data warehousing, data integration, cloud design, and data modeling.
Develop programs in Python and SQL.
Work with event-based and streaming technologies to ingest and process data.
Work with structured, semi-structured, and unstructured data.
Optimize Databricks jobs for performance and scalability with big data workloads.
Monitor and troubleshoot Databricks jobs and resolve issues or bottlenecks.
Implement data management, security, and governance best practices in the Databricks environment.
Design and develop enterprise data warehouse solutions.
Write SQL queries and programs, including stored procedures, and reverse engineer existing processes.
Perform code reviews to assess requirements fit, execution patterns, and adherence to established standards.
Lead an enterprise-wide Cloud Data Platform migration.