Machinify

Machinify

Senior Data Engineer - Analytics

Remote - US · Senior

Sponsorship not specified$170k-$200kDetected 1 day ago
PythonGitSQLBigQuerySnowflakeRedshiftDatabricksSparkAirflowdbtData EngineeringData VisualizationLLMsStatisticsExcelUnitySharePoint

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odds of building a lasting career here

61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

17 transfer filings in the last year, covering 17 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country.
  • You'll sit with the people who run our business, learn how the work actually happens, and turn that into certified models, metric definitions that survive scrutiny, and reports people use.
  • Our analytics warehouse unifies four platforms into one measurement model across dozens of unique client workflows.

Responsibilities

  • 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
  • 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.
  • 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.
  • Own a real greenfield problem. We're building a governed semantic layer that centralizes business logic. It's a funded priority and one of the highest-impact problems on the team.
  • See your work reach the business. This team owns the work all the way to the reporting layer, so you'll see how your decisions affect real business users.
  • Own a real greenfield problem.
  • We're building a governed semantic layer that centralizes business logic.
  • You can focus on solving new problems instead of building basic engineering discipline from scratch.
  • This team owns the work all the way to the reporting layer, so you'll see how your decisions affect real business users.

Requirements

  • 6+ years across analytics engineering, BI engineering, data engineering, or business analysis, with production ownership of the models and metrics you built.
  • You have opinions about project structure and can defend them.
  • 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.
  • Comfort with high autonomy in a fast, async, Slack-first environment.
  • We participate in E-Verify as required by applicable law.
  • Expert SQL and strong dimensional modeling instincts. You spot a grain mismatch in someone else's model before you run it.
  • Production dbt: models, tests, macros, exposures, documentation, and CI. You have opinions about project structure and can defend them.
  • Hands-on with a cloud lakehouse or warehouse. Databricks and Spark SQL preferred
  • Real visualization talent. You've owned a BI semantic layer and the reports on top of it, not just the tables underneath. Power BI and DAX strongly preferred
  • Looker/LookML, Tableau, MetricFlow, or Cube are credible substitutes. Bring dashboards you designed and be ready to say what you left out.
  • Stakeholder fluency. 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. When two numbers disagree you don't average them, escalate them, or trust the newer one. You find out why.
  • 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. You decide inside your lane and inform, rather than queuing decisions for permission.

Nice to have

  • 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.
  • Hands-on with a cloud lakehouse or warehouse.
  • Databricks and Spark SQL preferred
  • Snowflake, BigQuery, or Redshift transfer well.
  • Real visualization talent.
  • You've owned a BI semantic layer and the reports on top of it, not just the tables underneath.
  • Power BI and DAX strongly preferred
  • Looker/LookML, Tableau, MetricFlow, or Cube are credible substitutes.

Compensation

  • $170,000 - $200,000
  • In accordance with applicable state laws, we do not inquire about salary history during the recruitment process.
  • The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc.

Benefits

  • Full Medical/Dental/Vision for employees & their families
  • Flexible and trusting environment where you'll feel empowered to do your best work
  • Competitive salary, equity, 401(k) including employer match
  • Salary is one component of the total compensation package, which includes meaningful equity, excellent healthcare, flexible time off, and other benefits and perks.

Company info

  • What We Offer - Work from anywhere in the US!
  • We are hiring for different levels, and our Recruiting team will let you know if you qualify for a different role/range.
  • We are proud to be an equal opportunity workplace.

Equal opportunity

  • If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know.

Visa & Work Authorization

  • al employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status
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This listing is sourced directly from Machinify's careers page and normalized into a canonical job model.