• Design, build, and support reliable ELT/ETL pipelines on Microsoft Azure. • Partner with data architects, BI developers, and business stakeholders to land ERP and operational data into our lake/warehouse. • Monitor jobs, triage incidents, perform root‑cause analysis, and execute break/fix and performance tuning. • Ensure data quality via validation checks, schema enforcement, and automated tests; document lineage and business rules. • Collaborate with BI developers and business partners to translate requirements into optimized data sets for consumption. • Hardening and improving CI/CD (Azure DevOps), environments, and runbooks for compliant delivery. • Contribute to standards (naming, partitioning, coding patterns) and knowledge base articles/playbooks for on-call support.

About Helm Health Helm is a Series A start-up transforming health insurance with "Dynamic Copay" – a new insurance plan that lets members see simple, upfront prices for all medical care before making decisions. Our team is building the infrastructure to power these plans for health insurance payors. With Helm, our clients offer simpler health plans to their members, helping them navigate to higher-value care. Our team has specialized in Dynamic Copay solutions since 2020, and Helm is the only independent platform in the market. We have grown rapidly since our launch, working with clients from local health plans to the nation's largest health insurers. The market is forming around us, making it an exciting time to join! Role Overview We're seeking a Senior Backend Engineer to join our Data team. You'll work alongside our Principal Data Engineer to build and improve the automated systems that power our data infrastructure — pipelines, data quality, integrations, and internal tooling that make the rest of the engineering org more effective. Responsibilies - Design and build automated data pipelines and ETL/ELT processes - Improve data quality, validation, and monitoring across production systems - Build internal tooling that accelerates engineering workflows and reduces manual data operations - Work across PostgreSQL and BigQuery to optimize storage, query performance, and data modeling - Collaborate with engineering teams across the org to understand data needs and build scalable solutions - Participate in code reviews and architecture discussions - Contribute to the on-call rotation for data systems - Support data governance and access control practices to ensure compliance with HIPAA and other regulatory requirements across data systems - Maintain clear documentation for data pipelines, schemas, and system dependencies to support team knowledge sharing and operational continuity - Experience with dbt (data build tool) or similar SQL-based transformation frameworks Requirements - 5+ years in backend or data engineering - Strong Python proficiency - Strong SQL skills, particularly in PostgreSQL and BigQuery - Experience designing and maintaining automated data pipelines - Experience with data quality frameworks, validation, and monitoring - Docker/Kubernetes - Google Cloud Platform Preferred Qualifications - Go proficiency - Experience with additional data stores at scale (CouchDB, CockroachDB, or similar) - Health insurance or claims processing experience - Terraform/Terraform Cloud - Incident management and response experience - Start-up experience Characteristics - Self-directed and comfortable working across systems to find and fix data problems - Mission-driven — motivated by making healthcare simpler and more transparent - Willing to ask questions and admit what you don't know - Systems thinker — you see how data flows through an organization and instinctively look for ways to make it better Internal Tools/Technology - Cursor / Linear / GitHub / Notion / Whimsical - Slack / Google Workspace / Zoom - incident.io / Sentry - Claude, ChatGPT, Gemini — we are an AI-forward engineering team - macOS / Linux Compensation The target base salary range for this position is $150,000 - $225,000 and is part of a competitive total rewards package including equity and benefits. Individual pay may vary from the target range and is determined by several factors, including experience, skills, location, internal pay equity, and other relevant business considerations. Benefits/Offerings - Unlimited PTO (mandatory 12 days) - Computer + home office stipend - 401(k) + matching - Medical, dental, and vision insurance - Autonomy and tons of room for career growth Occasional Travel We meet quarterly as a company. Please note that this is a fully remote opportunity.

Role Description This position is term limited with an anticipated end date of approximately 12 months from the date of hire. This position is eligible for State employee benefits and may be extended as the situation warrants. We’re looking for a strategic and collaborative Data Architect to advise, develop and facilitate data architecture strategy including cloud, advanced technologies & platforms for OIT and partner agencies. In this role you will support efforts as an expert and leverage technology and innovation to provide scalable solutions to complex and diverse business problems. You will approve all relevant data architecture decisions and ensure alignment with agency needs, considering both the current and future needs of the agency. - Consulting as a resource on data strategy and architecture to OIT and agency partners. - Driving innovations, collaborations, and insights establishing a strong data-driven approach to decision-making across the organization. - Bringing best in class technologies, innovation, and creativity to the table in developing technical solutions to solve complex multi-dimensional problems. - Providing technology expertise by architecting, prototyping, researching, recommending, documenting, and assisting in implementing and evaluating technical solutions for business issues whether purchased or developed. - Assessing new data initiatives to determine compliance with the architecture, information security and data standards. - Interfacing with vendor technology/solutions, as well as appropriate involvement of OIT architecture, throughout the entire project lifecycle. Qualifications - A minimum of five (5) years of experience in data architecture (solution architecture), data management and information classification at the enterprise level, including an understanding of common information architecture frameworks and information models. - Demonstrated experience designing solutions in modern data technology platforms including Cloud (Snowflake, AWS, Azure, GCP, Spark) based solutions. - Experience in developing and operationalizing architectural and data designs, including data, technology and infrastructure. - Experience with identifying, monitoring, and rectifying data quality concerns using data governance tools. Requirements - Additional appropriate education will substitute for the required experience on a year-for-year basis, but cannot completely substitute for these qualifications. - Training or Certification related to the work assigned to the position will be assigned credit towards substitution for experience and/or education, but cannot completely substitute for these qualifications. - If the minimum qualifications include a degree requirement, additional appropriate paid or unpaid experience will substitute for the required education on a year-for-year basis. Benefits - This position may require travel within the specified geographic area, and to locations across the state as needed. - This position may require on-call duties as needed by the position.

About Us dbt Labs is the pioneer of analytics engineering, helping data teams transform raw data into reliable, actionable insights. Since 2016, we’ve grown from an open source project into the leading analytics engineering platform, now used by over 90,000 teams every week, driving data transformations and AI use cases. As of February 2025, we’ve surpassed $100 million in annual recurring revenue (ARR) and serve more than 5,400 dbt Platform customers, including AstraZenica, Sky, Nasdaq, Volvo, JetBlue, and SafetyCulture. We’re backed by top-tier investors including Andreessen Horowitz, Sequoia Capital, and Altimeter. At our core, we believe in empowering data practitioners: - Reliable, high-quality data is the fuel that propels AI-powered data engineering.
 - AI is changing data work, fast. dbt’s data control plane keeps data engineers ahead of that curve. - We empower engineers to deliver reliable, governed data faster, cheaper, and at scale. dbt Labs is now synonymous with analytics engineering, defining the modern data stack and serving as the data control plane for enterprise teams around the world. And we’re just getting started.. We’re growing fast and building a team of passionate, curious people across the globe. Learn more about what makes us special by checking out our values. As a Senior Data Engineer at dbt Labs, you'll build and maintain the core data platform infrastructure that powers our internal analytics and data products. You'll own the platform that makes data trustworthy at every layer — from the contracts that govern how it lands, to the infrastructure that stores, transforms, and delivers it across the business. This role is a part of a tight-knit, strategic team that combines strong technical execution with a bias for impact and cross-functional influence. This is a unique opportunity to work on infrastructure that sits at the center of how dbt Labs runs as a business — with executive visibility, deep cross-functional reach, and the added dimension of dogfooding the very products we build. If you're excited by the challenge of solving hard platform problems with cutting-edge tooling and making a direct, lasting impact on company growth, this role is for you. In this role, you can expect to: - Own the architecture and operations of our data lakehouse, including object storage, table formats, maintenance, and query engine integrations - Build and maintain the infrastructure layer that transforms and serves data reliably at scale—from raw landing zones through to curated, queryable datasets - Partner with product engineering to establish data contracts and schema standards around event telemetry, ensuring data arrives in the lakehouse in a form that's reliable and ready for downstream use - Drive decisions on data platform architecture, tooling, and engineering best practices across storage, compute, and access layers - Enhance observability and monitoring of data infrastructure, including pipeline reliability, data freshness, and system performance - Partner cross-functionally with teams across Analytics, Infrastructure, and Product to understand data needs and deliver impactful platform solutions - Provide product feedback by dogfooding new data infrastructure and AI technology You're a great fit if you have: - Expert-level SQL and Python skills - 5+ years of experience as a data engineer, and 8+ years of total experience in software engineering (including data engineering roles) - Strong knowledge of data lakehouse architecture, including storage layer design, table formats, and compute/query engine integration - Experience defining and enforcing data contracts or schema standards in collaboration with upstream engineering teams - Hands-on experience with modern orchestration tools like Airflow, Dagster, or Prefect - Working knowledge of cloud infrastructure tooling, including Terraform, Helm, and Kubernetes - A bias for action—able to stay focused and prioritize effectively in an ambiguous environment You'll stand out if you have: - Experience developing and scaling dbt projects - Hands-on experience with Apache Iceberg or other open table formats in production, including multi-region or multi-cloud deployments - Experience designing platform infrastructure that serves multiple downstream teams and use cases - Experience working in a SaaS or high-growth tech environment Remote Hiring Process: - Interview with a Talent Acquisition Partner - Interview with Hiring Manager - White boarding session with a member of the data team - White boarding session with a member of the software engineer team - White boarding session with a cross functional stakeholder - Final wrap up/ values discussion with Data Leader Compensation: We offer competitive compensation packages commensurate with experience, including salary, equity, and where applicable, performance-based pay. Our Talent Acquisition Team can answer questions around dbt Lab’s total rewards during your interview process. In select locations (including Boston, Chicago, Denver, Los Angeles, Philadelphia, New York City, San Francisco, Washington, DC, and Seattle), an alternate range may apply, as specified below. - The typical starting salary range for this role is: - $147,000 - $178,000 - The typical starting salary range for this role in the select locations listed is: - $163,000 - $198,000 Benefits: - Unlimited vacation time with a culture that actively encourages time off - 401k plan with 3% guaranteed company contribution - Comprehensive healthcare coverage - Generous paid parental leave - Flexible stipends for: - Health & Wellness - Home Office Setup - Cell Phone & Internet - Learning & Development - Office Space dbt Labs is an equal opportunity employer, committed to building an inclusive team that welcomes diverse perspectives, backgrounds, and experiences. Even if your experience doesn’t perfectly align with the job description, we encourage you to apply—we value potential just as much as a perfect resume. Want to learn more about our focus on Diversity, Equity and Inclusion at dbt Labs? Check out our DEI page. dbt Labs reserves the right to amend or withdraw the posting at any time. For employees outside the United States, dbt Labs offers a competitive benefits package. RSUs or comparable benefits may be offered depending on the legal or country limitations. Privacy Notice Supplement to Privacy Notice - Californians Supplement to Privacy Notice - EEA/UK