Role Description - Analyze business workflows and identify opportunities for data automation and AI-driven process automation. - Design, build, and maintain scalable data pipelines and integrations, including ingestion from unreliable or unstructured 3rd party sources. - Build LLM- and agent-based solutions for data transformation, validation/testing, and extraction tasks. - Containerize data and AI workloads using Docker and deploy to cloud infrastructure (AWS). - Develop prototypes and POCs to validate ideas quickly — both data pipelines and AI-powered workflows. - Collaborate with business and technical teams to refine requirements and iterate on solutions. - Support the deployment and integration of data and AI solutions into production systems. - Continuously improve data processes through automation and AI-driven approaches. - Contribute to data modeling, quality, and observability practices. Qualifications - 3+ years of experience in Data Engineering. - Strong data engineering background with the ability to design and own solutions end-to-end. - Proficiency in Python, Airflow, dbt, and Redshift for data processing, pipeline development, and transformation. - Experience building and maintaining ETL / ELT pipelines and data integrations, including fetching and normalizing data from non-robust 3rd party sources. - Hands-on experience with LLM/agent-based automation applied to business processes (e.g., building agents or LLM-powered workflows for data transformation, testing, or extraction). - Practical familiarity with modern AI tooling — LLM APIs (OpenAI, Anthropic, etc.), RAG patterns, prompt engineering, and agent frameworks (LangChain, LlamaIndex, or similar). - Cross-functional flexibility: comfortable stepping beyond pure DE work into adjacent areas — light DevOps (Docker, CI/CD, cloud deployment), backend integration, and basic frontend when a POC requires it. - Excellent communication skills — able to explain technical decisions to non-technical stakeholders. - Self-directed and proactive: able to spot workflow inefficiencies and drive improvements with minimal supervision. - Product thinking: collaborate with business teams, propose solution approaches, build quick POCs, iterate on feedback, and support production deployment. Requirements - 3+ years of experience in Data Engineering. - Strong data engineering background with the ability to design and own solutions end-to-end. - Proficiency in Python, Airflow, dbt, and Redshift for data processing, pipeline development, and transformation. - Experience building and maintaining ETL / ELT pipelines and data integrations, including fetching and normalizing data from non-robust 3rd party sources. - Hands-on experience with LLM/agent-based automation applied to business processes (e.g., building agents or LLM-powered workflows for data transformation, testing, or extraction). - Practical familiarity with modern AI tooling — LLM APIs (OpenAI, Anthropic, etc.), RAG patterns, prompt engineering, and agent frameworks (LangChain, LlamaIndex, or similar). - Cross-functional flexibility: comfortable stepping beyond pure DE work into adjacent areas — light DevOps (Docker, CI/CD, cloud deployment), backend integration, and basic frontend when a POC requires it. - Excellent communication skills — able to explain technical decisions to non-technical stakeholders. - Self-directed and proactive: able to spot workflow inefficiencies and drive improvements with minimal supervision. - Product thinking: collaborate with business teams, propose solution approaches, build quick POCs, iterate on feedback, and support production deployment. Benefits - Direct cooperation with the already successful, long-term, and growing project. - Flexible work arrangements. - Collaborative and supportive team culture. - Truly competitive salary. - Help and support from our caring HR team.

Role Description We are looking for a talented and analytically minded Data Engineer to join our growing team. In this role, you will be at the heart of our data ecosystem; designing and maintaining robust data pipelines, managing our cloud-based data lake on AWS, and transforming raw data into clean, reliable datasets that power business-critical reporting and analytics. Key Responsibilities - Design, build, and maintain scalable ETL/ELT pipelines using orchestration tools such as Apache Airflow, dbt, or equivalent frameworks. - Extract data from diverse sources (APIs, databases, streaming systems) into our AWS-based data lake. - Transform raw, unstructured data into clean, well-modelled datasets ready for analytics and reporting. - Own and evolve our data lake architecture, including multi-zone S3 storage and AWS Glue cataloguing. - Manage relational and non-relational databases, ensuring optimal schema design, indexing, and query performance. - Leverage AWS services (S3, Redshift, Glue, Lambda, EMR) to build scalable, cost-efficient data solutions. - Process and analyse large-scale datasets using big data technologies such as Apache Spark. - Collaborate with analysts and business stakeholders to translate reporting requirements into reliable data models. - Contribute to the design and evolution of our overall data architecture, data governance, and quality standards. - Document systems, data flows, and architectural decisions to a high standard. Qualifications - Proven experience as a Data Engineer or in a similar data-focused engineering role. - Strong proficiency in Python for data engineering tasks; experience with Rust is a significant advantage. - Hands-on experience building and maintaining ETL/ELT pipelines, ideally using Apache Airflow. - Deep knowledge of database management - both relational and non-relational. - Solid experience with AWS cloud services relevant to data engineering (S3, Glue, Redshift, EMR, Lambda, IAM). - Experience working with big data platforms and distributed computing frameworks (e.g. Apache Spark). - Strong understanding of data lake architecture, including storage layers, partitioning, and data cataloguing. - Excellent analytical thinking and problem-solving ability - you enjoy digging into complex data challenges. - Ability to communicate technical concepts clearly to non-technical stakeholders. Bonus Points - Experience with Rust for performance-critical data processing. Benefits - Opportunity to shape the data architecture of a growing organisation from an early stage. - Opportunity to be a thought leader with a wide span of control in a fast-growing startup with experienced mentors. - A challenging and rewarding environment where you can directly impact the future of the company and the industry.

Data Modeler Location: Sterling Heights United States Job Description: Sterling Heights, MI Contract - 1st Shift, 9/80 Pay Rate: $61.22/Hr Benefits: overtime, medical, dental, vision, 401k Travel: 10% - Hybrid: 3 days in office, 2 remote REQUIREMENTS: Data Modeler - Bachelor's degree in data management, Data Science, Math, Statistics or equivalent - Minimum 6 years of relevant experience - Excellent oral and written communications. - Be directly involved in developing data models and process flows as well as liaising with multiple stakeholders - mainly engineering, to document and/or validate the current state or As-Is business process. - Proven ability to work within teams in which your contributions are critical to success. - Proficiency with tools such as Power BI, Visual Basic, MS Excel, MATLAB/Simulink, Mathcad, MagicDraw, Midas, AWS/AWS Redshift, SSAS, Alation, Dataiku, Oracle, SQL. - Experience using entity-relationship diagrams (ERDs), dimensional modeling, normalization techniques, and metadata repositories to design and document data structures. - Understanding of data warehousing concepts. - Experience with big data technologies like Hadoop or Spark. - Familiarity with cloud-based data services such as AWS or Azure. - Background in data governance and data quality concepts. - Excellent problem-solving and analytical skills. - Strong communication and collaboration skills with both technical and non-technical stakeholders. - Experience in Agile or Scrum environments. JOB DESCRIPTION: Data Modeler Work as part of a team designing, building, and maintaining data infrastructure, ensuring accurate and timely data accessibility for teams and applications, often involving large datasets and complex systems. You will be responsible for creating and maintaining data models that serve as blueprints for a Combat Mission System's data pipeline and associated management strategy. You will translate complex business requirements into structured data representations, ensuring that data flows seamlessly across systems and supports analytics, reporting, and operational needs. Their work is critical for maintaining data integrity, consistency, and accessibility. Key Responsibilities: Data Modeler - Design and implement conceptual, logical, and physical data models to represent organizational data accurately. - Collaborate with business analysts, data architects, developers, and other stakeholders to gather requirements and ensure models meet business and technical needs. - Maintain a central data dictionary, enforce data standards, and ensure compliance with data governance policies. - Optimize performance of data infrastructure by tuning data models for efficiency, reduce redundancy, optimize reusability at the right levels and improve database performance. - Design solutions for integrating data across systems and perform reverse engineering of existing databases when necessary. - Develop and maintain documentation, naming conventions, and coding standards to ensure consistency across data systems helping the business to define "what does good look like?" - Ensure that data is stored securely, efficiently, and in a manner that is accessible for analysis and reporting. - Ensuring the accuracy, consistency, and reliability of data, implementing data validation and quality control processes. - Optimize data pipelines for speed, scalability, and performance, ensuring that data is available when and where it's needed. - Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and ensure that data infrastructure meets their needs. - Troubleshoot issues with data infrastructure, monitor system performance, and perform regular maintenance to ensure smooth operation. - Support configuration control, documentation and change impact analysis on the businesses data architecture model including identification of Authoritative Source Of Truth (ASOT) databases, connectors to replicate data from ASOTS to Midas and/or AWS Cloud Environments through data transformation within Power BI. SKILLS PREFERRED: Data Modeler - Experience with structured problem-solving techniques - Knowledge of technical requirements and systems relevant to Combat Vehicles - Experience working with development teams - Knowledge of metrics related to Agile and use of them to report back to team members at all levels - 1+ years of Scrum/Agile management - In-depth knowledge of Engineering and/or manufacturing environments EXPERIENCE PREFERRED: Data Modeler - 10 or more years of relevant work experience EDUCATION PREFERRED: Data Modeler - Master's degree in mathematics, statistics, business, engineering, physical/applied sciences, or management discipline (business administration, accounting, finance, economics or management information technology)

Title: Data Engineer - Optum Advisory Board - Remote Location: Eden Prairie, Minnesota Requisition number: 2361893 Job category: Technology Primary location: Eden Prairie, MN 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 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. At Advisory Board, part of Optum Insight, we've helped health care industry leaders work smarter and faster by providing provocative insights, data and analytics, and practical tools to support execution for over 40 years. Our core products include research and analytics membership, events, expert support, custom research, and sponsorship. Learn more about Advisory Board. The Quantitative Insights team powers the industry-leading data and analytics capabilities core to Advisory Board's value proposition. In this position within Advisory Board's data team, you will design, develop, test, and deploy enterprise ready data pipelines and architectures to support the Advisory Board's data and analytics research technology projects, ranging from small enhancements to major new projects. You will develop scalable and maintainable ETL processes, ensure data quality/security, and collaborate with data scientists to optimize analytics infrastructure. The position will play a critical role in all data technology initiatives as we continue this amazing journey of modernizing and innovating our data and technology ecosystem in support of our new and exciting business transformation. Data solutions you build will power analytics tools used by providers across the country to improve efficiency and deliver better care. 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: - Pipeline Development: Design, build, and maintain scalable, reliable, and efficient ETL/ELT pipelines using AWS Glue, Python, and SQL. Automate manual processes and optimize PySpark jobs for big data - Data Lake/Warehouse Management: Architect and manage data lakes (AWS S3), data warehouses (Redshift, S3 Tables) and relational databases (PostgreSQL, SQL Server). Use data modeling best practices to ensure data is accurate, accessible, and organized for efficient reporting and analysis - Cloud Infrastructure: Utilize AWS services like ECS and Lambda for data ingestion and orchestration tasks, involving a variety of external systems (Kafka, Snowflake, Databricks, custom API, etc.) - Data Quality & Security: Implement monitoring and troubleshooting measures to ensure data integrity and security, including IAM policies and CloudWatch logging - Collaboration: Work closely with data scientists and analysts to understand healthcare data and business requirements, and support data-driven decision-making - Analytics Development: Build data sets and dashboards, configure RLS and user permissions, and optimize dashboard performance on Amazon Quick Suite. Configure parameters for interop with web app embedding - CI/CD: Leverage GitHub for version control, code review, and automated deployment of pipelines across environments 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: - 8+ years of solid experience in data engineering using Python or PySpark - 5+ years of experience with AWS including Glue, Lambda, IAM, Redshift - 3+ years developing and optimizing PySpark jobs with proven big data experience - 3+ years of best practices in data analysis and modeling - Experience optimizing the architecture for big data, query performance, ease of use, and data governance - Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement - Experience working with Cloud technologies (AWS preferred) - Proven solid expertise in SQL and data modelling with relational databases like SQL Server, Postgres etc. Preferred Qualifications: - Experience in Amazon Quick Suite developing datasets and dashboards with support for web app embeddings - Understanding of health care claims data, including Medicare and commercial datasets - Proven eagerness and willingness to learn new technologies - Proven solid analytical, problem solving and decision-making skill - Demonstrated depth of health care knowledge and expertise - Proven written and oral communication skills *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.