Requisition Number: 2373873 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. Optum Government Solutions (OGS) partners with federal and state agencies to modernize health and human services programs through data, analytics, and technology. OGS supports large scale Medicaid Enterprise Data Warehouse (EDW), analytics, and federal reporting programs that enable program integrity, regulatory compliance, and data driven decision making for state agencies. Optum is seeking a hands on Senior Data Engineer (ETL / Python Developer) to support the Enterprise Data Warehouse (EDW) and Analytics Program. This role plays a critical part in designing, developing, and maintaining scalable data ingestion and transformation pipelines that support Medicaid analytics, federal reporting, and enterprise decision support. The ideal candidate brings solid ETL and Python engineering expertise, Teradata experience as well as experience working with large healthcare datasets, and the ability to operate effectively in a regulated, audit sensitive environment. This is a delivery focused role requiring close collaboration with architects, analysts, QA, PMs, SMEs, developers, and reporting BI teams across both legacy and cloud based platforms. 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 enterprise ETL pipelines using Azure Data Factory (ADF), Informatica PowerCenter, and Python based frameworks - Build and optimize scalable data processing solutions using Python, Spark, and Databricks - Support Medicaid analytics and federal reporting initiatives (e.g., T MSIS, PERM, MARS, Quality of Care) - Develop robust data validation, reconciliation, and audit traceable data pipelines - Write and optimize SQL and stored procedures across relational platforms such as Snowflake, Oracle, and SQL Server - Participate in cloud migration and modernization initiatives within Azure based architectures - Collaborate with analysts, QA, and reporting teams to ensure data quality, accuracy, and timeliness - Follow data engineering best practices for performance, reliability, reusability, and security - Support production operations, incident resolution, and root cause analysis - Participate in code reviews, source control, and CI/CD processes using Azure DevOps and GitHub 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 data engineering experience with a focus on enterprise data warehousing - 5+ years of hands on ETL development using Informatica PowerCenter, Azure Data Factory, or similar tools - 5+ years of Python development for data engineering and automation - 5+ years of Teradata experience - 3+ years of experience with Spark based processing frameworks (Databricks or equivalent) - Solid SQL expertise and experience with relational databases (such as Snowflake, Oracle, SQL Server) - Experience with source control and DevOps practices (Azure DevOps, GitHub, CI/CD) - Proven solid analytical, problem solving, and troubleshooting skills - Ability to travel periodically based on project or customer needs Preferred Qualifications: - Azure certifications related to data engineering or analytics - Experience supporting State Medicaid EDW or MMIS analytics environments - Healthcare or public sector analytics experience (Medicaid / Medicare preferred) - Data modeling experience in enterprise data warehouse environments - Scripting experience (PowerShell, Bash) for automation and orchestration - Experience designing or consuming APIs (REST) within data platforms - Familiarity with data quality frameworks, reconciliation, and audit support *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. 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.

• Architect, build, and own Overflow's core data infrastructure from the ground up — pipelines, warehouses, data models, and orchestration • Design and implement scalable ETL/ELT pipelines that collect, transform, and deliver clean, reliable data across Overflow's platform and business functions • Build and maintain a unified data layer that integrates data across Engineering, Product, Finance, Revenue, Success, and Operations • Design well-structured, intuitive data models that empower self-service analytics across the company and power OLAP views in customer facing applications • Build and maintain dashboards and reporting infrastructure that give leadership real-time visibility into key business metrics — total giving volume, client sentiment, payment revenue • Partner with the Head of AI to design storage schemas and organization strategies for semi-structured and unstructured data, providing the clean structures required to power advanced MLOps, RAG pipelines, and agent memory • Implement Databricks Unity Catalog to establish strict data governance, documentation standards, access controls, and role-based visibility across the organization. • Build for reliability by implementing data quality monitoring, alerting, and validation frameworks to ensure data accuracy and trustworthiness. • Collaborate closely with Engineering, Product, Finance, Payment Ops, Support, and RevOps to understand data needs and deliver scalable solutions • Act as the internal expert and advocate for data — educating teams on best practices and helping them ask better questions of the data • Contribute to the product roadmap by surfacing data-driven insights about customer behavior, platform performance, and market opportunity

Role Description The Senior Manager, Data Engineering will play a critical role in revitalizing OTG’s data analytics platform and strategy, transforming how data is leveraged across operations, finance, and guest experience. This role will serve as a hands-on leader responsible for building and modernizing OTG’s data platform, driving scalable data solutions, and enabling real-time insights that power business decisions across the organization. This individual will help define the future state of OTG’s data ecosystem, ensuring it supports growth, operational efficiency, and innovation. In this Role you will… - Lead the design and execution of a modern data platform strategy, aligned with OTG’s business goals and growth trajectory - Drive the revitalization and modernization of data pipelines, data models, and data infrastructure - Build and optimize scalable ETL/ELT pipelines to support high-volume transactional data from POS, operations, and customer systems - Establish a roadmap for data architecture, data governance, and analytics enablement - Ensure data systems support real-time insights, operational reporting, and advanced analytics use cases - Partner with Engineering, Product, Finance, and Operations teams to translate business needs into data-driven solutions - Define and enforce data engineering standards, best practices, and governance frameworks across the organization - Lead the migration and modernization of legacy data systems into cloud-based platforms - Oversee data quality, data integrity, and system reliability across the enterprise - Manage and mentor a team of data engineers, driving performance, accountability, and growth - Provide hands-on technical leadership, including coding, troubleshooting, and architectural design as needed - Collaborate with external vendors and partners to support delivery and scalability initiatives Qualifications - Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience) - 6–10+ years of experience in data engineering, data architecture, or related technical roles - 2–4+ years of leadership experience, managing engineering teams or technical initiatives - Proven experience building and scaling modern data platforms in cloud environments (AWS, Azure, or GCP) - Strong background working in high-volume, data-intensive environments (hospitality, retail, QSR, or similar preferred) Requirements - Data Platform Modernization & Transformation - Data Engineering & ETL/ELT Pipeline Development - Cloud Data Architecture (Snowflake, Databricks, Redshift, Synapse, etc.) - Real-Time Data & Streaming (Kafka or similar) - Data Governance & Data Quality Management - Cross-Functional Stakeholder Collaboration - Hands-On Technical Leadership - Team Leadership & Talent Development - Problem Solving & Continuous Improvement - Communication & Organizational Agility Company Description On the Go (OTG) has elevated the dining and retail experience for travelers by bringing together world-class hospitality, award-winning dining concepts, and forward-thinking technology. With more than 300 unique dining and retail locations across North America’s busiest airports, we’re fueled by a passion for creating exceptional guest experiences—made possible every day by our incredible Crewmembers. At OTG, people truly come first. We invest in our teams and foster growth in an exciting, fast-paced environment where everyone can shine. How we work is just as meaningful as what we accomplish. Our values—Care, Continuous Improvement, Quality, and Teamwork—guide the way we show up for our guests and for each other. We are committed to fostering an inclusive, safe, and dynamic workplace where individuals feel empowered to contribute and grow.

Role Description Your Mission - Design the target-state data architecture: Postgres CDC → Kafka → Snowflake → client-facing data products. - Own tooling decisions across ingestion, orchestration, transformation, and quality layers. - Implement CDC-based ingestion from PostgreSQL services (RDS, Aurora, EC2, K8s operator) using Debezium or equivalent. - Build streaming and near-real-time pipelines with defined SLAs. - Build a data quality control layer: checksums, reconciliation, schema validation, anomaly detection, and alerting. - Define quality checkpoints across the full pipeline — from source capture through Snowflake to client delivery. - Define and enforce data contracts with service-owning teams for core entities: transaction, merchant, settlement, and processing status. - Build the external data delivery layer: financial settlement, transaction status, processor reconciliation, and client analytics. - Design tenant separation and implement replay/reload mechanisms for failure recovery. - Start hands-on, then gradually hire and grow a small data engineering team as the function matures. - Build a pragmatic roadmap with concrete deliverables at 3, 6, and 12 months. Qualifications - 5+ years in data engineering with end-to-end ownership of production pipelines. - Hands-on with Snowflake, PostgreSQL CDC (Debezium preferred), and Kafka. - Solid AWS experience — S3, RDS, Aurora, and cloud data infrastructure. - Data quality engineering mindset: monitoring, reconciliation, lineage. - Comfortable defining data contracts and driving requirements with backend engineering teams. - Technical leadership experience: project ownership, cross-team alignment, delivery under constraints. - Kubernetes, Airflow/Prefect/Dagster, and dbt are strong pluses. - Payments domain knowledge — settlement, transaction lifecycle, processor integrations — is a strong plus. - Familiarity with gRPC, RabbitMQ, and reading Go/Python service code is expected. - English language skills at the B2 level and fluent Russian language. Benefits - An opportunity to make something great even greater, you can be the reason why we grow, develop, and become the best fintech company on the market! - Career prospects - we are young, we have huge ambitions, and it is important that our employees grow with us. - Work with coworkers who are passionate about their business. - Compensation that will fully correspond to the competence and knowledge, with yearly performance reviews. - Remote work. - 20 days of vacation time; bank holidays; sick leaves; additional birthday day off.