Requisition Number: 2351455 Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep expertise in the industry and innovative technology empower us to help organizations reduce costs while improving risk management, quality and revenue growth. Ready to help us deliver results that improve lives? Join us to start Caring. Connecting. Growing together. We are seeking a skilled and motivated Senior ETL / Data Integration Developer to join our team. This role is responsible for designing, developing, and delivering scalable ETL frameworks and components within a multi terabyte Oracle Exadata environment that integrates encounter and enrollment data from New York State (NYS) healthcare plans. In this role, you will synthesize and integrate large, complex datasets to support the management, evaluation, and analysis of the NYS healthcare system, including the New York All Payer Database (APD). This is a hands on technical role requiring deep expertise in data integration, transformation, data quality, and performance optimization using enterprise ETL and data integration platforms. Exposure to modern or cloud based data platforms is desirable. You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. Primary Responsibilities: - Design, develop, and maintain ETL workflows, pipelines, and mappings to load healthcare data into NY APD reporting structures - Apply ETL development best practices, including parameterization, reusable components, modular design, and avoidance of hard coded logic - Build reusable frameworks and automation to reduce manual operational activities and improve reliability - Perform optimization, troubleshooting, and debugging of ETL processes across development, test, and production environments - Develop and execute unit, system, and integration testing for ETL pipelines - Tune and optimize ETL jobs for performance, scalability, and throughput; collaborate with data modelers and DBAs on architecture and data model optimization - Provide development support and conduct code reviews and walkthroughs to ensure adherence to standards and best practices - Enforce secure coding principles and data protection standards in accordance with State of New York policies - Document and maintain technical designs, ETL specifications, and operational procedures - Troubleshoot pre production and production ETL job failures and data quality issues - Perform data profiling, validation, reconciliation, and balancing checks to ensure data accuracy and completeness - Design and implement data quality checks and controls across ingestion, transformation, and load phases You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications: - 5+ years of hands on experience designing, developing, and supporting ETL / data integration solutions using any enterprise grade ETL or data integration tool (on prem, hybrid, or cloud) - 5+ years of experience with Oracle databases and PL/SQL, including solid SQL development and performance tuning skills - 2+ years of experience with scripting or programming languages (eg, Python, Shell, or similar) - 2+ years of experience in data analysis, validation, and reconciliation - 2+ years of healthcare data experience, including Medicaid, Medicare, Exchange, or commercial payer data - Experience with data modeling techniques for data warehouse and analytical environments - Proven experience supporting large scale, high volume data processing environments - Solid understanding of data warehouse architecture, database design principles, and ETL patterns - Proven excellent problem solving skills, attention to detail, and ability to work independently and collaboratively - Proven solid communication and documentation skills Preferred Qualifications: - Experience with Informatica ETL suite - Experience or familiarity with modern or cloud based data platforms and ETL technologies (eg, Snowflake, Databricks, Azure, AWS, or similar) - Experience working with EDI healthcare transactions, including 834, 837, and NCPDP - Advanced experience working in large Oracle Exadata or high performance database environments - Experience implementing data quality frameworks, auditability, and reconciliation controls in regulated data environments - Experience using AI/LLM models to support data engineering (eg, accelerating SQL/ETL development, automating documentation, enabling data quality anomaly detection, or generating data pipeline templates) in a secure and compliant manner - Exposure to modern data engineering patterns, such as ELT, scalable batch processing, or hybrid architectures - Knowledge of HIPAA and healthcare regulatory security requirements *All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $91,700 to $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable. Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants. At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission. UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.

Role Description As an ETL Data Engineer, you will play a critical role in our client’s expanding data engineering team, designing, developing, and maintaining data integration processes primarily using Python (PySpark) and Azure Synapse Analytics to ensure the accuracy and availability of analytical data. - Develop and maintain ETL data engineering processes using Python (PySpark) within Azure Synapse Analytics Notebooks, and/or Azure Synapse Analytics Pipelines. - Apply your expertise in data warehousing, understanding star schemas, facts, and dimensions, to design and build effective data storage structures in a Massively Parallel Processing (MPP) SWL Pool. - Extract data from various sources, including REST APIs, SQL database tables, and CSV files. - Utilize your deep knowledge of Azure Synapse Analytics to design and optimize data notebooks/pipelines for scalability and performance. - Contribute to the implementation and understanding of other Data Fabric concepts, such as data lakes, lakehouses, delta lakes, and data cataloging. - Collaborate with data architects to create data models and schemas that align with business requirements. - Implement data quality checks and validation processes to maintain data accuracy and consistency. - Identify and resolve performance bottlenecks and optimize ETL data notebooks/pipelines to meet SLAs. - Monitor ETL jobs, diagnose issues, and implement solutions to ensure data pipeline reliability. - Maintain comprehensive documentation of ETL data engineering processes, data flows, and data transformations. - Work closely with cross-functional teams to understand data requirements and provide support for data-related initiatives. - Ensure data security and compliance with data governance and privacy standards. Qualifications - Bachelor’s degree in Computer Science, Information Technology, or a related field; or equivalent work experience, with certifications related to data engineering or data science (e.g. Azure Data Engineer) being a plus. - Proven experience in ETL data engineering with significant expertise in using Python (PySpark) to perform data extraction, transformation, and loading from REST APIs, SQL database tables, and CSV files. - Proficiency in using Azure Synapse Analytics resources including Notebooks, Pipelines, Linked Services, and Azure Key Vault. - Demonstrated ability to write complex SQL queries, optimize query performance, and work with both SparkSQL and MS SQL. - Knowledge of data integration best practices and tools. - Experience with version control systems, such as Git (Azure DevOps). - Strong problem-solving and analytical skills, with a keen attention to detail. - Excellent communication skills, both verbal and written, with the ability to work collaboratively in a team environment with shifting priorities. - Familiarity with big data technologies, machine learning, and data analysis preferred. - Experience with data visualization tools (e.g. Power BI, Tableau) and Agile Methodologies a plus. Benefits - Your contributions are highly valued by clients, and the work you do often has a direct and significant impact on their business. - You will have the opportunity to work on a variety of projects for our incredible clients, which will accelerate your career growth. - You’ll collaborate with modern technologies and work alongside some of the best professionals in the industry!

• Fachliche und disziplinarische Führung des Data-Engineering-Teams • Aufbau, Konzeption und Weiterentwicklung moderner Datenplattformen und Data-Lakehouse-Architekturen (z. B. auf Basis von Databricks) • Strategische Beratung unserer Kunden bei der Einführung und Skalierung datengetriebener Plattformen in unterschiedlichen Branchen • Entwicklung und Optimierung von ETL-/ELT-Pipelines zur Verarbeitung großer Datenmengen in Batch- und Streaming-Szenarien • Sicherstellung von Qualität, Best Practices und technischer Exzellenz im Team – von Code Reviews über Architekturentscheidungen bis hin zu Standards für DataOps und CI/CD • Aktive Mitgestaltung der Unit-Strategie, des Portfolios sowie Unterstützung bei Go-to-Market- und Pre-Sales-Aktivitäten

• Design, build, and maintain scalable batch and near-real-time data pipelines using cloud-native services • Develop and optimize data ingestion, transformation, and orchestration workflows across diverse data sources • Build and maintain ELT/ETL frameworks to support analytics, reporting, and data science use cases • Prepare, transform, and curate raw data into analytics-ready datasets for both technical and non-technical stakeholders • Develop, deploy, and operate data products within Azure-based analytics platforms (e.g., Databricks, Synapse, Fabric) • Implement data quality checks, monitoring, and observability to ensure data accuracy, reliability, and integrity • Apply data governance, security, and privacy controls aligned with enterprise and regulatory standards • Monitor data platform performance and proactively implement cost and performance optimizations • Partner with data scientists, analysts, and analytics engineers to ensure trusted and timely access to data • Design data solutions that are scalable, reusable, automated, and well-governed by default