Azure Data Engineer

We’re seeking a Cloud Data Engineer to support a financial services team in Metropark, NJ, focused on developing and optimizing scalable data pipelines and Azure-based cloud solutions. The ideal candidate will have 5+ years of experience with Python, SQL Server, large-scale data processing, and Databricks PySpark, and be available to work onsite three days per week.

• Build and maintain data pipelines to collect, transform, and load data from multiple sources while ensuring data accuracy and quality.
• Develop and deploy Spark applications in Databricks to process large-scale datasets.
• Work with Delta Lake, data warehousing, cloud platforms, data integration, and data modeling solutions.
• Write and maintain Python and SQL code to support data engineering and analytics initiatives.
• Design and support dimensional data models for enterprise data warehouse environments.
• Develop data solutions that leverage real-time and event-driven data processing technologies.
• Manage and process structured, semi-structured, and unstructured data across various platforms.
• Optimize Databricks workloads to improve performance, efficiency, and scalability.
• Troubleshoot Databricks jobs and resolve production issues, errors, and performance bottlenecks.
• Apply data governance, security, and data management best practices across the data environment.
• Design, build, and enhance enterprise data warehouse solutions.
• Create complex SQL queries, stored procedures, and enhancements to existing data processes.
• Participate in code reviews to ensure quality, performance, and adherence to development standards., Mid-sized, growing Financial Services firm based in Midtown Manhattan!Long term contract with competitive rate and opportunity for conversion!

We’re seeking a Cloud Data Engineer to support a financial services team in Metropark, NJ, focused on developing and optimizing scalable data pipelines and Azure-based cloud solutions. The ideal candidate will have 5+ years of experience with Python, SQL Server, large-scale data processing, and Databricks PySpark, and be available to work onsite three days per week., * 5+ years of experience developing solutions with Python.

• 5+ years of experience working with SQL Server and large-scale datasets.
• 5+ years of experience building and deploying ETL pipelines using Databricks and PySpark.
• Hands-on experience with cloud data warehouse platforms such as Snowflake, Synapse, Redshift, or BigQuery.
• Strong understanding of data warehousing concepts, including OLTP, OLAP, dimensional modeling, fact tables, and dimension tables.
• Experience supporting or leading cloud data platform migration initiatives.
• Strong data architecture and solution design skills.
• Experience working with cloud-based data, analytics, and messaging platforms.
• Cloud certification(s).
• Experience with workflow orchestration tools such as Airflow.