Senior Data Engineer

Machinify

. Design, build, and operate reliable, automated data pipelines for health plan data .

Posted 11/3/2026full-timeRemote • United StatesSenior💰 $180,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and operating automated data pipelines, with strong capabilities in data modeling and integration. Proficient in SQL, Python, and data quality practices, while effectively collaborating with cross-functional teams to support decision-making and enhance data workflows.

Highest-signal resume keywords

Data EngineeringSQLPythonData ModelingCI/CD Practices

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data Pipeline DesignData ModelingSQLPythonDbtWorkflow OrchestrationSpark SQLData QualityAutomated TestingIncident Response

Soft Skills

CollaborationProblem-SolvingAdaptabilityCritical ThinkingLearning Agility

Tools & Technologies

SnowflakeDatabricksAirflowCI/CD ToolsAutomated Testing Frameworks

Industry Keywords

Healthcare DataData IntegrationCanonical ModelsDimensional DesignData Governance

Tech Stack

Tools & technologies

AirflowPythonSnowflakeSparkSQL

About the role

Key responsibilities & impact

Design, build, and operate reliable, automated data pipelines for health plan data
Model complex healthcare data into canonical and analytical models
Migrate legacy processes, pipelines, and models into a common platform while preserving existing logic and behavior
Extend and integrate tools and workflows for adoption by other teams
Implement data quality and software engineering practices, including validation, automated testing, code review, and CI/CD
Document engineering work and critically review AI-generated work
Own pipelines end to end, including ingestion, modeling, quality, deployment, and day-to-day operations
Support decision-making and claims payment outcomes
Partner with ML, Product, Analytics, Platform, Operations, and Customer teams
Drive the lifecycle of core datasets powering the platform
Contribute to customer onboarding and data integration

Requirements

What you’ll need

5+ years in data engineering, including production ownership of built pipelines
Strong SQL and Python
Strong data modeling, including canonical and dimensional design, conflicting sources, history, and adjustments
Production dbt and workflow orchestration (Airflow or similar)
Expertise with Snowflake and/or Databricks
Spark SQL experience
Data quality and CI/CD practices, including validation, reconciliation, pull requests, automated tests, and deployment automation
Ability to take broad, loosely defined problems end to end across ingestion, modeling, infrastructure, APIs, and operations, including incident response
Ability to onboard a new data source from discovery to delivery
Record of extending or integrating existing tools and building things other teams use
Ability to learn complex domains quickly and verify AI-generated code and abstractions against ground truth
Understanding of how to leverage AI in development and automation, including efficiency and potential risk

Benefits

Comp & perks

Work from anywhere in the US; digital-first environment
Full Medical/Dental/Vision for employees & their families
Flexible and trusting environment
Unlimited FTO
Competitive salary
Equity
401(k) including employer match
Meaningful equity
Excellent healthcare
Flexible time off
Other benefits and perks