Data Analyst - SQL, PySpark, ADF, Databricks, ETL

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Role Overview

A Data Engineer Consultant is responsible for designing, building, and optimizing data pipelines and architectures that support advanced analytics, reporting, and business intelligence. This role combines deep technical expertise with strategic consulting to help organizations unlock the value of their data assets.

Primary Responsibilities:

• Data Architecture and Engineering: Design and implement scalable data pipelines using tools like SQL, PySpark, Azure Data Factory, and Databricks
• ETL Development: Build and maintain robust ETL workflows to ingest, transform, and load data from various sources into data lakes or warehouses
• Cloud Integration: Leverage cloud platforms (Azure, AWS, GCP) for data storage, processing, and orchestration
• Data Quality and Governance: Ensure data accuracy, consistency, and compliance with enterprise standards
• Stakeholder Collaboration: Work closely with business analysts, data scientists, and product teams to translate business needs into technical solutions
• Performance Optimization: Tune data systems for performance, scalability, and cost-efficiency
• Mentorship and Best Practices: Guide junior engineers and promote best practices in data engineering and agile delivery
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

• Education: Bachelor's or Master's in Computer Science, Engineering, or related field
• Experience: 3+ years of experience in data engineering roles, with 2+ years in a consulting or client-facing capacity
• Technical Proficiency:
  • SQL, Python, PySpark, Scala
  • Azure Data Factory, Databricks, Synapse
  • Data warehousing (Snowflake, Redshift, BigQuery)
  • CI/CD pipelines and DevOps practices
• Soft Skills: Proven solid communication, problem-solving, and stakeholder management abilities

• Experience with AI/ML data pipelines or MLOps frameworks
• Familiarity with data privacy regulations and compliance frameworks
• Demonstrated ability to assess and improve existing data architectures