Role Description Function Health is building the most comprehensive picture of human health ever assembled and making sense of that data is core to our mission. We're looking for a Staff Analytics Engineer to own the semantic layer that sits at the heart of our data platform: the trusted, well-modeled foundation that powers dashboards, self-serve analytics, and increasingly, AI-driven data agents. This isn't a greenfield "figure out what to build" role. We have a platform. Now we need someone to make it exceptional, clean models, a well-governed metrics layer, and the architecture to let AI query our data reliably and accurately. You'll collaborate closely with data scientists, product engineers, and business leaders to ensure that when anyone (or anything) asks a question about our data, they get the right answer. This is a fully remote role. Function Health is a distributed team, we hire across the US. Key Responsibilities - Own the semantic layer: Design and maintain the metrics, dimensions, and data models that serve as the single source of truth across the business — built to be queried by humans and AI alike. - Architect for AI-readiness: Structure our Databricks and GCP-based data platform so it can reliably power AI-driven analytics agents — clean schemas in Unity Catalog, consistent naming conventions, and strong data contracts. - Drive data quality end-to-end: Build observability, testing, and alerting into pipelines so we catch problems before stakeholders do. - Enable self-serve analytics: Partner with product, clinical, and business teams to deliver tooling and dashboards that let them answer their own questions without filing tickets. - Set the standard: Establish and enforce data modeling conventions, documentation practices, and code review norms across the data org. - Collaborate cross-functionally: Translate ambiguous business questions into data solutions; work with product engineering to improve event logging and measurement coverage. Qualifications - 8+ years of analytics engineering or data engineering experience, with clear progression to staff-level scope and impact. - Deep SQL expertise and strong Python skills. - Strong data modeling fundamentals — you know what clean, extensible, well-documented models look like and can build and enforce that standard regardless of tooling. Experience with dbt is a plus. - Experience with modern data stack tools: Databricks, Snowflake or BigQuery, Airflow or similar orchestration, Looker/Tableau or equivalent BI tools. - Track record of building resilient, monitored, production-grade data systems — not just pipelines that work, but ones that stay working. - Strong communicator who can make technical tradeoffs legible to non-technical stakeholders. Requirements - Bias Toward Action: Demonstrated ability to take initiative, make decisions under uncertainty, and move projects forward even in the face of ambiguity. - Entrepreneurial Spirit: Strong adaptability to changing business needs with a knack for building and optimizing processes. - Communication: Excellent communication skills, capable of explaining complex technical concepts to non-technical stakeholders. - Remote Work Adaptability: Comfort with remote work environments, demonstrating the ability to stay productive and connected with the team irrespective of physical location. - Continuous Improvement: A willingness to question assumptions and a commitment to continuous improvement. Nice-to-Have Skills and Experiences - Experience with health tech or regulated data environments (HIPAA, PHI/PII handling). - Familiarity with Databricks Unity Catalog, Delta Lake, or Spark. - Experience building or integrating with AI/LLM-powered analytics tools or data agents. - GCP experience. Core Values - Ruthless Prioritization: We don’t let perfect get in the way of progress. - Member-First, Always: We design and deliver like we’re caring for someone we love. - One Team, Moving Fast: We are aligned in purpose, prioritization, and speed. - Radical Ownership, Relentless Execution: We don’t just ship– we own outcomes and drive results. - Mission Over Ego: We are ruthlessly aligned to our mission– and leave ego at the door. - Sustained Integrity in Every Detail: We earn trust by obsessing over accuracy, quality, and clarity in everything we do. Benefits - Competitive salary and benefits package. - Flexible working hours. - Dynamic work environment where creativity and innovation are encouraged. Important Notice Legitimate communication from the Function Health team will always come from an email address ending in @functionhealth.com. Function Health will never request personal information such as banking details or payment during the hiring process. Please be cautious of communications or job offers that come from other email domains, instant messaging platforms, or unsolicited calls. If you ever have doubts about the legitimacy of a communication, please reach out to us directly at talent@functionhealth.com.

Role Description We at Coforge are hiring a Lead Data Engineer with the following skill set. - Lead and mentor a team of data engineers, setting technical direction, conducting code reviews, and promoting engineering excellence. - Own the end-to-end architecture and design of the data platform, ensuring scalability, reliability, and alignment with business needs. - Take full ownership of implementation delivery, from design through deployment, ensuring high-quality, production-ready solutions. - Define and drive the data migration strategy from Snowflake / SSIS to Azure Databricks and DBT, including architecture decisions and execution oversight. - Collaborate closely with cross-functional stakeholders (data, product, architecture, and business teams) to translate requirements into robust technical designs. - Design and oversee the development of scalable data pipelines and data models, ensuring best practices in performance and maintainability. - Lead the implementation of infrastructure-as-code using Terraform, enforcing consistency and automation across environments. - Establish and enforce architectural standards, design patterns, and engineering best practices across the data ecosystem. - Ensure reliable and efficient data integration between Legacy system and Azure environments, with strong focus on data quality and observability. - Drive CI/CD adoption and oversee release processes for data pipelines and platform components. - Act as the primary technical owner for troubleshooting complex issues and ensuring long-term stability of the platform. - Maintain comprehensive documentation of architecture, design decisions, and implementation standards. Qualifications - Proven experience owning system design and leading implementations of large-scale data platforms. - Strong hands-on expertise with Snowflake, Azure Databricks, and DBT with strong Python. - Will have worked on large scale data transformations comprising of thousands of DBT models and data pipelines handling terabytes of data daily. - Deep understanding of data architecture, data modelling, and distributed data systems. - Extensive experience with Terraform and infrastructure-as-code principles. - Demonstrated experience leading cloud-to-cloud data migration projects (AWS to Azure preferred). - Strong experience with CI/CD pipelines and Git-based version control. - Advanced SQL skills and deep knowledge of ETL/ELT frameworks. - Strong problem-solving skills with the ability to make architectural trade-offs and decisions. - Excellent communication skills, with the ability to influence both technical and non-technical stakeholders. - Ability to thrive in a fast-paced, ownership-driven environment. - Previous experience in the insurance or financial sector industry, with strong understanding of core domains such as claims, policies, underwriting, and risk. - Will have managed teams with a level of maturity and able to demonstrate key success outcomes with these teams. - Will have managed low, mid and top performers within the team to get the best from them via mentoring, development and training needs where needed. Preferred Skills - Experience implementing data governance, observability, and quality frameworks. - Strong knowledge of security and compliance standards in insurance or financial services. - Experience with real-time and streaming data technologies (Kafka, Event Hubs, Delta Live Tables). - Familiarity with lakehouse architecture and cost/performance optimization strategies. - Experience operating in multi-cloud or hybrid cloud environments. Company Description At Coforge, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

Role Description Are you passionate about building robust data infrastructure and enabling innovation through engineering excellence? As our Data Engineer, your goal is to own and evolve the foundation of our data infrastructure. You will be central in ensuring data reliability, scalability, and accessibility across our lakehouse and transactional systems. This role is ideal for someone who thrives at the intersection of engineering and innovation, ensuring our data platforms are robust today while enabling the products of tomorrow. A Day in the Life - Lakehouse and Pipelines - Design, build, and operate reliable ETL and ELT pipelines in Python and SQL. - Manage ingestion into Bronze, standardization and quality in Silver, and curated serving in Gold layers of our Medallion architecture. - Maintain ingestion from transactional MySQL systems into Vaniam Core to keep production data flows seamless. - Implement observability, data quality checks, and lineage tracking to ensure trust in all downstream datasets. - Data Modeling and Governance - Develop schemas, tables, and views optimized for analytics, APIs, and product use cases. - Apply and enforce best practices for security, privacy, compliance, and access control, ensuring data integrity across sensitive healthcare domains. - Maintain clear and consistent documentation for datasets, pipelines, and operating procedures. - Integration of New Data Sources - Lead the integration of third-party datasets, client-provided sources, and new product-generated data into Vaniam Core. - Partner with product and innovation teams to build repeatable processes for onboarding new data streams. - Ensure harmonization, normalization, and governance across varied data types (scientific, engagement, operational). - Analytics and Predictive Tools - Collaborate with the innovation team to prototype and productionize analytics, predictive features, and decision-support tools. - Support dashboards, APIs, and services that activate insights for internal stakeholders and clients. - Work closely with Data Science and AI colleagues to ensure engineered pipelines meet modeling and deployment requirements. - Reliability and Optimization - Monitor job execution, storage, and cluster performance, ensuring cost efficiency and uptime. - Troubleshoot and resolve data issues, proactively addressing bottlenecks. - Conduct code reviews, enforce standards, and contribute to CI/CD practices for data pipelines. Qualifications - 5+ years of professional experience in data engineering, ETL, or related roles. - Strong proficiency in Python and SQL for data engineering. - Hands-on experience building and maintaining pipelines in a lakehouse or modern data platform. - Practical understanding of Medallion architectures and layered data design. Requirements - Familiarity with modern data stack tools, including: - Spark or PySpark - Workflow orchestration (Airflow, dbt, or similar) - Testing and observability frameworks - Containers (Docker) and Git-based version control - Excellent communication skills, problem-solving mindset, and a collaborative approach. Benefits - 100% remote environment with opportunities for local meet-ups. - Positive, diverse, and supportive culture. - Passionate about serving clients focused on Cancer and Blood diseases. - Investment in you with opportunities for professional growth and personal development through Vaniam Group University. - Health benefits – medical, dental, vision. - Generous parental leave benefit. - Focused on your financial future with a 401(k) Plan and company match. - Flexible Time Off policy for rest and relaxation. - Volunteer Time Off for community involvement. - Emphasis on Personal Wellness. - Virtual workout classes. - Discounts on tickets, events, hotels, child care, groceries, etc. - Employee Assistance Programs. - Salary offers are based upon several factors including experience, education, skills, training, demonstrated qualifications, location, and organizational need. The range for this role is $110,000 - $125,000.

Role Description Our client is a plaintiff-side personal injury firm representing injured people and their families throughout California. We are headquartered in Century City, with offices serving the San Bernardino and Fresno markets. We run our practice on data, and we are hiring an engineer to own the systems that capture it. We use a connected stack of tools to track our metrics, data, KPIs, and marketing spend: - Domo for business intelligence and dashboards - Filevine for case management - Lead Docket for intake and lead tracking - AI tools, especially Claude, for automation Your job is to set it up, code it, connect it, and keep it running. This is a hands-on builder role, not a help-desk position. You will work directly against these platforms' APIs and webhooks, write the code and transformations that move and shape our data, build the dashboards and reports leadership relies on, and ship AI-driven workflows that save the firm time. You take requirements and turn them into working systems. Responsibilities - Build and maintain integrations across Filevine, Lead Docket, Domo, and our AI tools using their REST APIs, webhooks, and native connectors. - Filevine: Work with the Filevine API (v2), webhook subscriptions, and the Data Connector to pull case, project, contact, and financial data into our reporting layer. - Lead Docket: Configure and maintain the native Filevine sync, phase and field mapping, the open API, and webhooks; build out lead-source tracking and marketing ROI reporting. - Marketing attribution: Set up and maintain UTM parameters and similar tracking to capture the source when a prospective client reaches our website. - Domo: Ingest data through connectors, the Streams API, and custom connectors; build and maintain Magic ETL dataflows and Beast Mode calculations. - AI and Claude: Build automation and AI-assisted workflows using the Anthropic API and related tools. - Translate firm requirements into reliable, documented systems, working independently from a clear spec to a working build. - Monitor data pipelines for accuracy and uptime, troubleshoot breakages, and fix them quickly. - Document configurations, integrations, and workflows. - Maintain strict data security, access controls, and confidentiality across every system. Qualifications - Demonstrated experience building and maintaining API integrations, including REST APIs, OAuth authentication, and webhooks. - Hands-on coding ability in Python and/or JavaScript, plus working knowledge of SQL. - Experience building dashboards and reports in a business intelligence platform; Domo experience is strongly preferred. - Experience designing and maintaining ETL or data pipelines. - A track record of taking business requirements and independently delivering working systems. - Working knowledge of marketing attribution and tracking, including UTM parameters. - A serious data-security mindset and the discipline to handle confidential information appropriately. Preferred - Direct experience with Filevine and/or Lead Docket. - Experience integrating AI or large language models, especially the Anthropic (Claude) API. - Law firm or legal industry experience. - Familiarity with integration platforms (Workato, Zapier, Make) and cloud storage (AWS S3, Azure Blob). - Experience with the Domo Developer toolset or CLI.