Senior Data Engineer - Analytics

Posted Yesterday
Hiring Remotely in United States
Remote
170K-200K Annually
Senior level
Machine Learning • Software
We develop software that helps people get the right medical care, at the right time, at the right price.
The Role
Own the analytics data layer by translating stakeholder needs into certified dimensional models, governed metrics, semantic layers, dashboards, and reports. Build with dbt, SQL, Databricks, Power BI, and Airflow while ensuring data quality, observability, reconciliation, documentation, and dependable orchestration. Partner closely with finance, operations, and client-facing teams, automate recurring workflows, and use AI-assisted engineering practices in a fully remote environment.
Summary Generated by Built In

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. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.

As a Senior Data Engineer (Analytics) you own the layer where messy operational data becomes a number a business leader will act on. 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.

This is a data modeling and measurement enabling role more than a pipeline development role, though such skills will be helpful. Expect real time on calls with finance, operations, and client-facing teams, and real time in dbt, SQL, and Power BI. If you won’t ship a dashboard you can’t reconcile, you’ll fit in great.

What You’ll Do

  • 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.

What You Bring

  • 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. 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; 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. 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.
  • Strong writing. Much of your impact is a document, a definition, or a chart someone reads without you in the room.

Bonus points for

  • 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.

Why Join Us

  • 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.
  • Strong engineering foundation. We already have 634 production models, 1,800+ automated tests, and strong CI guardrails. You can focus on solving new problems instead of building basic engineering discipline from scratch.
  • 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.
  • Work directly with stakeholders. Every project has a clear business owner and defined acceptance criteria, so you know who you’re building for and what success looks like.
  • Use AI in the actual engineering workflow. We’ve built agent-driven workflows into our day-to-day development process, and our delivery velocity has grown significantly as a result. If you’re interested in actually using AI to change how software gets built, you’ll have plenty of opportunity here.
  • Make an impact in healthcare. The systems you build help a large-scale healthcare payment integrity business understand and improve its performance.

What We Offer

  • 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
  • Competitive salary, equity, 401(k) including employer match

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.  We are hiring for different levels, and our Recruiting team will let you know if you qualify for a different role/range. Salary is one component of the total compensation package, which includes meaningful equity, excellent healthcare, flexible time off, and other benefits and perks. 

Pay range: $170,000 - $200,000

 
Equal Employment Opportunity at Machinify
 
We are committed to equal 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. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/

Skills Required

  • 6+ years of experience across analytics engineering, BI engineering, data engineering, or business analysis
  • Production ownership of data models and metrics
  • Expert SQL skills
  • Strong dimensional modeling skills
  • Production experience with dbt, including models, tests, macros, exposures, documentation, and CI
  • Hands-on experience with a cloud lakehouse or data warehouse
  • Experience with Databricks and Spark SQL, or transferable Snowflake, BigQuery, or Redshift experience
  • Experience owning a BI semantic layer and reports
  • Power BI and DAX experience
  • Experience with Looker, LookML, Tableau, MetricFlow, or Cube
  • Ability to lead requirements discussions with nontechnical stakeholders
  • Experience reconciling conflicting data and metrics
  • Git and pull-request experience
  • Python experience for API calls, file parsing, statistics, or report generation
  • Strong written communication and documentation skills
  • Ability to work autonomously in an asynchronous environment
  • Healthcare data experience, including claims, DRG, coding review, payment integrity, provider contracts, or revenue cycle
  • Experience with data contracts, schema enforcement, ODCS-style governance, or CI quality gating
  • Experience with Databricks Unity Catalog, lineage, and DBU cost accountability
  • Experience with paginated reporting, SharePoint, or Excel delivery
  • Experience working with AI coding agents and reviewing their output

Machinify Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Machinify and has not been reviewed or approved by Machinify.

  • Healthcare Strength Health coverage is described as employer-paid for employees with additional support for dependents, alongside dental, vision, mental health, and FSA/HSA options. Listings consistently depict comprehensive medical benefits.
  • Leave & Time Off Breadth Policies include unlimited PTO, paid holidays and sick time, and a weekly no‑meetings day. These elements indicate broad time‑off access alongside flexible scheduling.
  • Parental & Family Support Inclusive paid parental leave is stated at 14 weeks for birth and non‑birth parents. Family benefits are prominently featured across public materials.

Machinify Insights

Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: Dallas, TX
96 Employees
Year Founded: 2016

What We Do

Machinify is an AI start-up in the Healthcare space. Our software platform leverages the latest advances in machine learning, large language models, data analytics, and cloud processing to solve previously intractable problems in the healthcare industry impacting millions of lives.

Why Work With Us

We are a heavily cross-functional, collaborative diverse team working together to solve big problems that matter. If you are looking for an exciting environment where you'll be challenged to do the best work of your career, consider joining us!

Gallery

Gallery

Similar Jobs

Microsoft Logo Microsoft

Analytics Engineer

Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
Remote
United States
206870 Employees
106K-223K Annually
Remote or Hybrid
7 Locations
37 Employees
130K-165K Annually

Shield AI Logo Shield AI

Analytics Engineer

Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Remote
USA
120K-180K Annually

NVIDIA Logo NVIDIA

Senior Software Engineer

Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
In-Office or Remote
6 Locations
21960 Employees
184K-357K Annually

Similar Companies Hiring

Onshore Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
60 Employees
Revel Thumbnail
Aerospace • Hardware • Robotics • Software
Marina Del Rey, California
60 Employees
Blee Thumbnail
Artificial Intelligence • Marketing Tech • Software
New York, New York
30 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account