Note: The job is a remote job and is open to candidates in USA. Machinify is hiring a Senior Data Engineer (Analytics) to turn operational data into trusted models, metrics, and reporting for business users. The role partners with stakeholders across finance, operations, and client-facing teams, owning analytics modeling, visualization, observability, orchestration, documentation, and workflow automation.

Responsibilities

• Run discovery with business stakeholders. Find the real need behind the request and turn it into acceptance criteria you can build against
• Model noisy healthcare operational data into certified dimensional models across our Databricks bronze → silver → gold architecture in dbt and SQL. Our sources disagree with each other in ways that are interesting rather than trivial. Sorting that out is most of the job
• Own metric definitions. One measure, one definition, one place, documented so a non-engineer can read it. Today a single operating metric can be re-derived in a dozen models; collapsing that into a governed semantic layer is yours
• Build and own the visualization layer. Power BI semantic models, dashboards, and paginated reports, including refresh health and semantic-model currency. We want real visualization judgment: the right chart for the question, a hierarchy an executive can read in ten seconds, and a reason for every choice
• Own observability for your models. Freshness and latency detection, statistical anomaly detection, and value-drift monitoring, plus the data tests, regression guards, and CI checks that keep a defect you just fixed from coming back
• Own orchestration for what you build. dbt Cloud job design, Airflow DAGs, scheduling, dependency ordering, dependable incremental runs
• Write it down. Design documents, model documentation, a CI-enforced knowledge base, and business-readable handoff packets, so whoever inherits your work doesn’t have to re-derive it
• Automate the recurring work. We codify repeating work into repeatable, testable, AI-assisted workflows instead of checklists in someone’s notes. You should be comfortable directing LLMs and supervising what they produce

Skills

• 6+ years across analytics engineering, BI engineering, data engineering, or business analysis, with production ownership of the models and metrics you built
• Expert SQL and strong dimensional modeling instincts
• Production dbt: models, tests, macros, exposures, documentation, and CI
• Hands-on with a cloud lakehouse or warehouse
• You've owned a BI semantic layer and the reports on top of it, not just the tables underneath
• You can run a requirements conversation with a non-technical owner, turn a vague complaint into a testable definition, explain a data problem as business risk, and tell someone their metric is wrong without losing them
• A reconciliation reflex
• Git and pull-request discipline as normal practice rather than overhead
• Python where it's genuinely the right tool (API calls, file parsing, statistics, report generation), and the judgment to reach for SQL where it isn't
• Comfort with high autonomy in a fast, async, Slack-first environment
• Strong writing
• Databricks and Spark SQL preferred; Snowflake, BigQuery, or Redshift transfer well
• Power BI and DAX strongly preferred; Looker/LookML, Tableau, MetricFlow, or Cube are credible substitutes
• Healthcare data: claims (837/835/UB04), DRG and coding review, payment integrity, provider contracts, or revenue cycle
• Data contracts, schema enforcement, or ODCS-style governance; quality gating in CI
• Databricks Unity Catalog, lineage, and cost/DBU accountability
• Paginated reporting, SharePoint/Excel delivery, or other “the business needs it in exactly this format” surfaces
• Working alongside AI coding agents and reviewing what they produce against a contract you wrote

Benefits

• Work from anywhere in the US! Machinify is digital-first.
• Full Medical/Dental/Vision for employees & their families
• Flexible and trusting environment where you’ll feel empowered to do your best work
• Unlimited FTO
• Equity
• 401(k) including employer match

Company Overview

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