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. We are seeking a highly skilled Principal Data Engineer to lead the design, development, and optimization of large‑scale data platforms and analytical solutions. The ideal candidate will have deep expertise in MSSQL, AWS cloud services, Data Warehousing, Python, Airflow, and overall data management best practices, with a strong ability to lead teams, define architecture, and drive data strategy across the organization. You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges. Primary Responsibilities: - Technical Leadership - Architect, design, and implement scalable data platforms, pipelines, and ETL/ELT workflows - Lead end‑to‑end data engineering efforts, ensuring reliability, performance, and cost‑efficient data systems - Mentor and guide junior and senior data engineers, fostering a culture of technical excellence and collaboration - Collaborate with cross‑functional teams (analytics, product, engineering, business) to align data solutions with business goals - Data Engineering & Pipeline Development - Build, optimize, and maintain robust data pipelines using Python, SQL, and Apache Airflow - Manage large-scale data ingestion, transformation, and orchestration frameworks - Optimize database queries, stored procedures, and schema design in MSSQL and other SQL/NoSQL systems - Cloud & Infrastructure - Develop and manage cloud‑native data platforms using AWS services (S3, Glue, Lambda, RDS, Redshift, EC2, Step Functions, etc.) - Ensure high availability, disaster recovery, and monitoring of critical data workflows - Implement CI/CD, infrastructure‑as‑code, and DevOps practices for data engineering workloads - Data Warehousing & Modeling - Design and enhance enterprise data warehouses and data marts following industry best practices - Drive dimensional modeling, data partitioning, performance tuning, and metadata management - Ensure consistency and quality across analytical datasets and data sources - Data Governance & Quality - Establish data quality frameworks, lineage tracking, validation checks, and documentation - Implement governance standards including security, compliance, and access control - Partner with business stakeholders to define and enforce master data and reference data strategies - 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 related field - 10+ years of experience in Data Engineering, with at least 3+ years in a senior/principal‑level role - 7+ years of experience in MSSQL—query optimization, indexing, stored procedures, performance tuning - 7+ years of experience in Data Warehousing, ETL/ELT, and big‑data processing - 5+ years of hands‑on experience with AWS Cloud for data architecture and pipeline development - 5+ years of extensive experience with Airflow for workflow orchestration - 3+ years of experience in Python for data engineering (Pandas, PySpark, etc.) - 2+ years of experience in data management principles: governance, quality, lineage, and security Preferred Qualifications: - Excellent leadership, communication, and cross‑team collaboration skills. - Ability to translate business needs into scalable technical designs. *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

• Lead the analytics function across the studio and define the strategic direction for product and marketing analytics • Develop and improve analytical tools and approaches, identify growth opportunities, improve the quality of working with metrics, and make analytics practical and business-oriented • Lead and develop analytics processes: standardize approaches to data collection, metric interpretation, experiment evaluation, and forecasting • Define and develop A/B testing and experimentation methodology end-to-end — from experiment design to results analysis, ensuring reliable conclusions and well-grounded decisions • Collaborate with product, marketing, and technical teams, translating data into clear recommendations and helping to define product priorities • Drive a data-informed culture across the studio, increase the maturity of the analytical approach, and strengthen the role of metrics in product and marketing processes

Role Description - Senioridade real em Ciência de Dados, idealmente já atuando como Cientista de Dados Sênior - Também pode entrar no processo perfil Pleno muito maduro, com tempo consistente na função e repertório compatível - Alta autonomia e proatividade - Capacidade de trabalhar de forma mais individual, sem estrutura robusta de dados ao redor - Vivência com produtos ou contextos early stage - Boa capacidade de definir métricas, estruturar dados e operar em parceria com times de produto e engenharia - Boa comunicação e maturidade profissional - Disponibilidade para atuar remotamente - Preferência por candidatos de qualquer estado, desde que fora da cidade de São Paulo, para reduzir risco de perda futura com a volta ao presencial local Qualifications - Experiência com Python, Pandas e SQL, embora stack não tenha sido tratada como fator central - Experiência em construção de produto e estruturação de dados desde o início

• Advance our recommendation and personalization logic by designing and validating new statistical approaches - from improved segmentation models and engagement scoring to causal uplift estimation and multi-touch attribution. • Own the experimentation framework for the team: design rigorous A/B and multivariate tests, develop methodologies to handle complex measurement challenges (novelty effects, interference, long-term effects), and ensure results are interpreted correctly. • Tackle complex analytical problems that require going beyond descriptive statistics - building predictive models, running causal inference analyses, and decomposing metric movements into their drivers. • Partner closely with the Senior Analyst to turn user journey insights into statistically grounded targeting and personalization strategies. • Collaborate with the ML Engineering Data Scientist to ensure that statistical models and experimental findings can be produced and integrated into the recommendation engine. • Define and refine the metrics and success criteria used to evaluate personalization quality, ensuring we measure what actually matters for users and for the business. • Own the offline evaluation framework: build and maintain counterfactual evaluation methods, replay-based policy estimation, and offline screening pipelines that let the team assess 10 ideas offline for every 1 tested live - dramatically accelerating iteration speed. • Map and measure the interplay between editorial rules and personalization logic - systematically investigating when and how rules like hardcoded IP placements, content diversity constraints, or curated onboarding slots interact with ML-optimized recommendations, and designing experiments to quantify the trade-off. • Communicate complex statistical findings clearly and confidently to non-technical stakeholders, and advocate for methodological rigor across the team.