• Own product direction across analytics, data pipelines, and reporting systems • Define and execute a roadmap focused on scalability, data quality, and operational efficiency • Identify and drive modernization opportunities across legacy analytics workflows and tooling • Lead efforts to reduce manual processes, redundant validations, and siloed development • Translate complex data workflows into clear product requirements and deliverables • Partner with engineering to shape data models, ETL pipelines, and distributed processing systems • Ensure data products meet standards for accuracy, performance, and reliability • Drive improvements in data lineage, traceability, and documentation • Work closely with data engineers on PySpark, Databricks, and distributed systems design • Understand tradeoffs in data modeling, pipeline design, and performance optimization • Contribute to decisions on architecture, tooling, and platform evolution • Ensure alignment with cloud infrastructure, security, and governance requirements • Lead backlog prioritization across competing data and reporting needs • Balance short-term delivery with long-term system health • Drive coordination across engineering, analytics, and reporting teams • Ensure delivery meets timelines, quality expectations, and regulatory requirements • Identify gaps in current team structure, workflows, and ownership models • Drive integration of analytics work into core product teams to reduce silos and handoffs • Establish clear ownership across calculations, data modeling, reporting, and delivery • Improve team operating model to support predictable, scalable delivery • Build trust across complex stakeholder groups including technical and non-technical partners • Translate data concepts into clear business and program impact • Proactively manage risks related to data accuracy, delivery, and dependencies • Drive alignment across external partners and internal teams

ArchWell Health is a new, innovative healthcare provider devoted to improving the lives of our senior members. We deliver best-in-class care at comfortable, accessible neighborhood clinics where seniors can feel at home and become part of a vibrant, wellness-focused community. Our members experience greater continuity of care, as well as the comfort of knowing they will be treated with respect by people who genuinely care about them, their families, and their communities.  Duties/Responsibilities: - Build data integrations from internal and external sources to centralize data into a Data Warehouse environment. - Monitor data integration operations, data quality, troubleshoot, and resolve problems. - Profile data sources and map to target table formats. - Develop and monitor data quality processes and address problems. - Develop, unit test and system test integration components. - Create support documentation describing the functionality of the integrations. - Participating in technical design & requirements gathering meetings. - Participate in planning and implementing data integration and data migration activities. - Perform QA tests to ensure data integrity and quality. - Research data issues between source systems and the data warehouse. Required Skills/Experience: - Bachelor’s degree required; Master's degree (in data science, computer science or MIS, mathematics, engineering, or related field) preferred. - 5+ years of prior experience in Data Management / ETL / ELT / Data Warehousing - Experience in writing Data Quality routines for cleansing of data and capturing confidence score - Experience with master data management - Strong knowledge of Structured Query Language (SQL) and Transact-SQL (T-SQL) - Experience using scripting languages such as JavaScript or Python - Experience Healthcare data models, datasets, and source systems (e.g. EHR, claims, labs, etc.) - Experience with healthcare reference data (ICD, CPT etc.) - Experience with agile delivery methodologies - Data Modeling experience preferred. - Strong organizational, administrative, and analytical skills required. - Experience managing and working in cloud environments such as Amazon Web Services or Azure - Knowledge of HIPAA; ability to implement systems and processes in accordance with regulations - Excellent interpersonal communication skills, both written and verbal ArchWell Health is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to their race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected classification.

• Leverage your expertise to design and maintain data transformation pipelines • Manage databases and cloud infrastructure • Ensure data is accessible and efficiently processed • Focus on performance, scalability, and security for data systems • Collaborate closely with the product team to document business needs and transform them into clear, actionable technical requirements • Build and maintain scalable ELT pipelines for reliable data ingestion, transformation, and delivery • Design, optimize, and manage data models in Snowflake for performance, scalability, and clarity • Create and maintain DAGs to define pipeline tasks, dependencies, and schedules for automated workflows • Collaborate with DevOps to configure and manage AWS infrastructure supporting data storage, pipelines, and transformations • Monitor pipelines to resolve failures and improve stability and data quality • Document pipelines, DAGs, and models to support onboarding and knowledge sharing

• Own and operate our data warehouse, pipelines, and transformation layer • Design, build, and maintain scalable, reliable data pipelines that ingest data from across our platform and third-party sources, ensuring data is always available and trustworthy for downstream consumers • Partner with data scientists and analysts to deliver clean, well-documented datasets and optimize query performance so teams spend less time wrangling data and more time generating insights • Incrementally improve and modernize our existing data systems - you won't build everything from scratch, but you'll know how to assess what we have, prioritize what matters, and migrate thoughtfully • Implement data quality monitoring, alerting, and documentation practices that build trust across the organization