Senior Data Engineer

UnitedHealth Group; Hyderabad; On-site; Confidential; Full time

Job summary

Optum seeks a Senior Data Engineering Analyst to design and optimize large-scale cloud data pipelines. You will work with Azure Databricks, Apache Spark, Python, and Apache Airflow to orchestrate complex ETL workflows and migrate legacy systems to modern cloud solutions. Collaboration with peers and business stakeholders is essential.

You will mentor junior engineers, enforce data quality, and help drive healthcare data insights across the organization on a global scale.

Qualifications

• Bachelor's/Master's in Computer Science, Information Technology, or related field (or equivalent work experience).
• 3+ years of professional data engineering or related experience.
• 3+ years designing data pipelines with Spark and Python.
• 2+ years building cloud data solutions with Azure Databricks.
• 2+ years migrating legacy ETL like IBM DataStage and databases like Teradata.
• 1+ years using workflow schedulers such as Apache Airflow.

Responsibilities

• Design, develop, and optimize high-volume cloud data pipelines.
• Collaborate with stakeholders to translate data requirements into engineering solutions.
• Provide technical guidance and mentoring to junior engineers.
• Ensure data quality, governance, and robust ETL processes.
• Migrate legacy systems to modern cloud architectures.
• Evaluate trends to inform design and strategic innovations.

Skills

Communication skills

Mentoring

Stakeholder presentations

Education

Bachelor's/Master's in CS/IT

Tools

Azure Databricks

Apache Spark

Python

Apache Airflow

Teradata

IBM DataStage

Job description

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.

Position Summary

As a Senior Data Engineering Analyst on our technology team, you will design, develop, and optimize high-volume cloud-based data pipelines that drive critical healthcare business insights. In this role, you will work with advanced technologies including Azure Databricks, Apache Spark, Python, and Apache Airflow to orchestrate complex ETL workflows. You will collaborate with peers and business stakeholders to solve complex healthcare data challenges, migrating legacy systems to modern cloud solutions. If you are passionate about data innovation, building robust data architectures, and leveraging cutting‑edge technologies to impact healthcare on a global scale, we invite you to join our team.

Primary Responsibilities

• Leverage enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement
• Evaluate emerging trends to inform solution design and strategic innovation
• Design, develop, and maintain secure, scalable, and robust data pipelines using Azure Databricks, Python, and Apache Spark
• Extract, transform, and load (ETL) data from legacy platforms like Teradata and IBM DataStage into modern cloud-based data environments
• Orchestrate and schedule complex data workflows and ETL processes using orchestration tools (with a preference for Apache Airflow)
• Optimize data pipeline performance, troubleshooting bottlenecks, and ensuring data quality and integrity
• Collaborate with cross‑functional teams to translate business and data requirements into efficient engineering solutions
• Provide technical guidance, mentoring, and support to junior engineers within the team
• 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

Required Qualifications

• Bachelor's/master's degree (such as B.E, B. Tech, MCA, M. Tech, MS) in Computer Science, Information Technology, or a related field, or equivalent work experience (such as 4+ years of software/data development experience in lieu of a degree)
• 3+ years of professional experience in data engineering, database management, or software engineering
• 3+ years of experience designing and developing data pipelines using Apache Spark (PySpark or Scala) and Python
• 2+ years of experience building and optimizing modern cloud data solutions using Azure Databricks
• 2+ years of experience migrating or integrating legacy ETL platforms (such as IBM DataStage) and databases (such as Teradata)
• 1+ years of experience with workflow scheduling/orchestration tools (such as Apache Airflow, Autosys, or equivalent)
• Proven communication and presentation skills, with the ability to articulate technical details to stakeholders

Preferred Qualifications

• Experience building and orchestrating data integrations using Azure Data Factory
• Hands‑on experience utilizing generative AI tools (such as GitHub Copilot) to accelerate coding, unit testing, and documentation
• Experience writing and optimizing Unix Shell or Perl scripts
• Experience leading or mentoring a team of junior engineers
• Knowledge of healthcare domain datasets, particularly around Customer, Member, Claims, and Provider information