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Machinify · 15 hours ago

Senior Data Engineer

United States

Full-time

Remote

Senior Level

$180K/yr - $220K/yr

6+ years exp

Machinify is a leading healthcare intelligence company delivering value and efficiency to health plan clients. As a Senior Data Engineer, you will transform raw data into trusted datasets that drive operational decisions and collaborate with various teams to ensure data accuracy and performance.

Artificial Intelligence (AI)SaaSBig DataAnalyticsBusiness IntelligenceMachine LearningPredictive Analytics

H1B Sponsor Likely

Responsibilities

Design and implement robust, production-grade pipelines using Python, Spark SQL, and Airflow to process high-volume file-based datasets (CSV, Parquet, JSON)

Lead efforts to canonicalize raw healthcare data (837 claims, EHR, partner data, flat files) into internal models

Own the full lifecycle of core pipelines — from file ingestion to validated, queryable datasets — ensuring high reliability and performance

Onboard new customers by integrating their raw data into internal pipelines and canonical models; collaborate with SMEs, Account Managers, and Product to ensure successful implementation and troubleshooting

Build resilient, idempotent transformation logic with data quality checks, validation layers, and observability

Refactor and scale existing pipelines to meet growing data and business needs

Tune Spark jobs and optimize distributed processing performance

Implement schema enforcement and versioning aligned with internal data standards

Collaborate deeply with Data Analysts, Data Scientists, Product Managers, Engineering, Platform, SMEs, and AMs to ensure pipelines meet evolving business needs

Monitor pipeline health, participate in on-call rotations, and proactively debug and resolve production data flow issues

Contribute to the evolution of our data platform — driving toward mature patterns in observability, testing, and automation

Build and enhance streaming pipelines (Kafka, SQS, or similar) where needed to support near-real-time data needs

Help develop and champion internal best practices around pipeline development and data modeling

Qualification

PythonSpark SQLAirflowData pipeline designAWSData quality checksStreaming pipelinesCommunication skillsTeam collaborationProblem-solving

Required

6+ years of experience as a Data Engineer (or equivalent), building production-grade pipelines

Strong expertise in Python, Spark SQL, and Airflow

Experience processing large-scale file-based datasets (CSV, Parquet, JSON, etc) in production environments

Experience mapping and standardizing raw external data into canonical models

Familiarity with AWS (or any cloud), including file storage and distributed compute concepts

Experience onboarding new customers and integrating external customer data with non-standard formats

Ability to work across teams, manage priorities, and own complex data workflows with minimal supervision

Strong written and verbal communication skills — able to explain technical concepts to non-engineering partners

Comfortable designing pipelines from scratch and improving existing pipelines

Experience working with large-scale or messy datasets (healthcare, financial, logs, etc)