Azure Data Engineer

Michael Page; Woodbridge Township (NJ); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health benefits

Job summary

Michael Page is seeking a Cloud Data Engineer to join a financial services team in Metropark, NJ, onsite three days a week. You will develop scalable data pipelines, Databricks PySpark workloads, and Azure-based cloud solutions, leveraging Python and SQL Server across enterprise data platforms.

Ideal candidates have 5+ years with Python, SQL Server, Databricks PySpark, and data warehousing concepts, plus experience with cloud data warehouses and orchestration tools like Airflow.

Qualifications

• 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.
• Experience with workflow orchestration tools such as Airflow.

Responsibilities

• 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.

Skills

Python

SQL Server

Databricks PySpark

Tools

Databricks

Snowflake

Synapse

Redshift

BigQuery

Airflow

Delta Lake

Job description

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.

A Financial Sservices firm providing corporate banking, investment banking, trade finance, foreign exchange, and treasury services.

Description

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.

Profile

• 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.
• Experience with workflow orchestration tools such as Airflow.

Job Offer

• Access to Michael Page health benefits beginning on day-1 of employment.

MPI does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, marital status, or based on an individual's status in any group or class protected by applicable federal, state or local law. MPI encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants.