Data Engineer - Databricks

System One; Pittsburgh (Allegheny County); On-site; USD 110,000 - 165,000; Full time

Job summary

System One is seeking a Data Engineer - Databricks for a contract-to-hire role in Pittsburgh, onsite. You will help build modern, cloud-native data platforms on Microsoft Azure, with a focus on Unity Catalog, governance, and enterprise analytics in the Investment/Capital Markets domain.

The ideal candidate designs scalable data pipelines using Azure Databricks, PySpark, SQL, and Delta Lake, and collaborates with architects and analysts in an Agile environment to deliver secure, high-performance

Qualifications

• Minimum 5 years of hands-on experience with Azure Databricks and Spark.
• Strong knowledge of Unity Catalog and data governance.
• Experience with Delta Lake, ETL/ELT development, and Azure data services.
• Proficient in Python (PySpark) and SQL.
• Experience with Git & CI/CD practices in Agile environments.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Azure Databricks.
• Build and optimize ETL/ELT workflows with PySpark, SQL, and Delta Lake.
• Implement Unity Catalog to support enterprise data governance and security.
• Develop cloud-native data engineering solutions on Azure.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Optimize Spark jobs for performance, scalability, and cost efficiency.
• Ensure data quality, reliability, and compliance through monitoring and best practices.
• Support deployments, troubleshooting, and performance tuning.
• Participate in code reviews and technical documentation.
• Apply DevOps practices and cloud security principles in Azure environments.

Tools

Azure Databricks

Unity Catalog

Delta Lake

Azure Data Factory

ADLS Gen2

Git

CI/CD

Terraform/Bicep

Job description

Job Title: Data Engineer - Databricks

Duration : Contract to Hire

Location : Pittsburgh, PA

Work Mode : 5 Days Onsite

Job Description:

Join a high performing data engineering team responsible for building modern, cloud native data platforms on Microsoft Azure. This role offers the opportunity to design and implement scalable, secure, and high performance data solutions using Azure Databricks, with a strong focus on Unity Catalog, data governance, and enterprise analytics within the Investment/Capital Markets domain.

The ideal candidate is passionate about cloud data engineering, enjoys solving complex data challenges, and thrives in a collaborative Agile environment. This position provides the opportunity to work with the latest Azure data technologies while delivering impactful business solutions.

Duties and Responsibilities

• Design, develop, and maintain scalable data pipelines using Azure Databricks.
• Build and optimize ETL/ELT workflows leveraging PySpark, SQL, and Delta Lake.
• Implement and manage Unity Catalog to support enterprise data governance, security, metadata management, and fine-grained access control.
• Develop cloud native data engineering solutions on the Microsoft Azure platform.
• Collaborate with architects, business analysts, and cross functional teams to gather and translate business requirements into technical solutions.
• Optimize Spark jobs and data pipelines for performance, scalability, and cost efficiency.
• Ensure data quality, reliability, and compliance through validation, monitoring, and best practices.
• Support production deployments, troubleshooting, and performance tuning.
• Participate in code reviews, technical documentation, and continuous improvement initiatives.
• Apply best practices for cloud data engineering, security, and DevOps within Azure environments.

Required qualifications to be successful in this role

• Minimum 5 years of hands-on experience with Azure Databricks.
• Hands on experience with Unity Catalog is mandatory.
• Strong experience building enterprise scale data engineering solutions on Microsoft Azure.
• Expert level experience with Apache Spark (PySpark) and SQL.
• Strong experience with Delta Lake, ETL/ELT development, and data pipeline implementation.
• Experience with Azure data services such as Azure Data Factory, Azure Data Lake Storage (ADLS Gen2), and related Azure ecosystem services.
• Strong understanding of data governance, metadata management, security, and access control.
• Mandatory experience in the Investment/Capital Markets domain.
• Experience with Git and CI/CD practices.
• Excellent analytical, communication, and problem solving skills.
• Experience working in Agile/Scrum delivery environments.

Preferred Qualifications

• Databricks Certified Data Engineer (Associate or Professional).
• Microsoft Azure Data Engineer Associate (DP 203) certification.
• Experience with Infrastructure as Code (Terraform/Bicep).
• Experience implementing DevOps practices for Azure Databricks environments.
• Familiarity with Azure Purview/Microsoft Purview is a plus.

Ref: #404-IT Pittsburgh