• The Senior Data Engineer will own the data engineering function on K2Share's Federal Team, partnering with technical and product leadership to deliver data products that support mission-critical decision-making for federal agency clients. • Design and build relational data layers that handle OSCAL and other structured compliance data - including ingestion, validation, transformation, and export workflows that preserve fidelity to source schemas across the full data lifecycle • Design and maintain data models that support governance, risk, compliance, scoring, and reporting workflows for federal cybersecurity programs, with OSCAL as the connective layer across them - including long-term retention and archival policies that align with federal recordkeeping and audit requirements • Design and build big-data processing pipelines on Databricks (PySpark, Delta Lake, Unity Catalog) that normalize cybersecurity data from across federal agency environments and produce analytical layers for trend analysis, executive reporting, and cross-program insights • Optimize data systems for performance and cost - identifying I/O and compute bottlenecks, scaling compute responsibly, and balancing throughput against the cost discipline federal engagements require • Architect, build and maintain AWS data infrastructure that meets federal security and operational requirements - working across services such as S3, Bedrock, Lambda, Fargate, and EC2 in support of compliance and analytical workloads • Design and implement audit-ready data primitives - change capture, access controls, validation, and lineage — that support agency reporting and continuous monitoring needs • Lead AI-first development and responsible AI deployment on the data team - using AI development tools as a standard part of the engineering loop, prototyping AI-assisted compliance workflows, and designing the production AI systems behind them (RAG architectures, vector store management, conversational agents, prompt and output guardrails, and evaluation pipelines), in alignment with federal AI governance guidance (OMB, NIST AI RMF) • Engage with federal agency stakeholders and internal teams during requirement discovery, delivery, and ongoing support — translating compliance needs into data products and customer feedback into improvements

• Design, build, and maintain saleable data pipelines within Snowflake from multiple sources • Build and maintain medallion architecture (bronze/silver/gold layers) for data lake solutions • Design data models that support both businesses intelligence and AI requirements • Lead cloud-native data platform evolution, integrating Snowflake with AWS. • Collaborate with business analysts, data scientists, and stakeholders to understand data requirements and translate them into technical specifications. • Implement data quality frameworks and monitoring systems to ensure accuracy, completeness, and consistency of data assets. • Develop and maintain comprehensive documentation for data pipelines, models, and processes. • Optimize query performance and resource utilization to reduce costs and improve processing times. • Participate in on-call rotation to support production data systems and resolve incidents.

Title: Senior Software Engineer - Data Engineering Location: Brentwood, Tennessee Requisition number: 2360661 Job category: Technology Primary location: Brentwood, Williamson, TN Overtime status: Exempt Travel: No 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 diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. Primary Responsibilities: - Design, build, and operate scalable data engineering platforms using modern ETL/ELT frameworks, including Azure Data Factory, Delta Lake, and cloud-native pipelines - Architect modular, reusable data systems that support batch and streaming workloads, advanced analytics, and AI/ML use cases - Influence overall data and AI platform architecture, including lakehouse design, metadata management, and data quality frameworks - Develop and optimize PL/SQL, Python, and Unix-based data processing solutions for high-volume, low-latency data pipelines - Enable Generative AI use cases by designing structured and unstructured data pipelines to support NLP, prompt engineering, vectorization, and inference workflows - Drive code reusability and standardized data patterns across teams through shared frameworks, libraries, and design standards - Ensure mature DevOps and DataOps practices, including CI/CD, automated testing, monitoring, incident response, and cost optimization - Deeply analyze ambiguous business and data problems, translating them into robust data engineering and AI solutions that deliver measurable business value - Lead adoption of best practices in data modeling, pipeline design, security, and governance, especially in regulated environments - Continuously assessing and modernizing existing data platforms, improving performance, reliability, scalability, and AI readiness - Partner with business, analytics, data science, and product leaders to manage delivery in an agile framework, rapidly delivering insights and AI-enabled capabilities - Mentor and coach engineers in data engineering, cloud, and Generative AI technologies, raising overall team capability - Attract and grow talent through strong technical leadership, effective interviewing, community engagement, and training junior interviewers - Communicate complex data and AI concepts clearly to both technical and non-technical stakeholders, including leadership presentations and solution demos Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear directions on what it takes to succeed in your role as well as provide development for other roles you may be interested in. Required Qualifications: - Bachelor's degree in CS or IT or Software Engineering related field - 7+ years of Data Engineering experience building enterprise-scale ETL/ELT solutions (e.g., ADF, DataStage, Talend, or equivalent) - 4+ years of experience with Azure public cloud including Databricks and Snowflake - 3+ years of hands-on experience with Unix/Linux shell scripting for data processing and automation - 3+ years of experience with Oracle PL/SQL development for data transformation, performance tuning, and production workloads - 3+ years of production support experience, including on-call rotations, incident resolution, and root cause analysis - 2+ years of experience with high-level programming languages, such as Python, Java, or Node.js, with Python preferred Preferred Qualifications: - Excellent written and verbal communication skills, with the ability to explain data and AI concepts clearly - Prior technical or people leadership experience, including ownership of complex systems - Demonstrated experience mentoring and developing junior Engineers *All Telecommuters 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. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 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. #RPO #GREEN

• Design, build, and deploy large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies. • Lead system-wide architectural decisions, focusing on data flow, performance, and resilience. • Actively contribute to the codebase with high quality code. • Lead major technical initiatives, reduce technical debt and ensure the platform meets the reliability and scalability SLAs. • Collaborate with product and engineering teams and R&D management to define the technical roadmap, review architecture and mentor junior engineers