
1001 - 5000 employees
⚕️ Healthcare Insurance
🤖 Artificial Intelligence
☁️ SaaS
💰 $10M Series A - Machinify on 2018-10
Healthcare Insurance • Artificial Intelligence • SaaS
Machinify is a healthcare-focused AI platform and services company that reshapes healthcare payments and payment integrity. Its AI operating system unifies claims, medical records, contracts, and policies, and uses foundation models and task-specific agents to automate and improve coding, payment accuracy, recoveries, and cost avoidance. Machinify serves health plans (including 18 of the top 20), supports insourced, hybrid, or fully-managed deployments, and emphasizes measurable outcomes — reporting 85+ customers, 270M member lives covered, and $6B+ in annual cost avoidance and recoveries.
🕒 April 2
🇺🇸 United States – Remote
💵 $180k - $220k / year
⏰ Full Time
🟠 Senior
🚰 Data Engineer
🦅 H1B Visa Sponsor
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1001 - 5000 employees
⚕️ Healthcare Insurance
🤖 Artificial Intelligence
☁️ SaaS
💰 $10M Series A - Machinify on 2018-10
Healthcare Insurance • Artificial Intelligence • SaaS
Machinify is a healthcare-focused AI platform and services company that reshapes healthcare payments and payment integrity. Its AI operating system unifies claims, medical records, contracts, and policies, and uses foundation models and task-specific agents to automate and improve coding, payment accuracy, recoveries, and cost avoidance. Machinify serves health plans (including 18 of the top 20), supports insourced, hybrid, or fully-managed deployments, and emphasizes measurable outcomes — reporting 85+ customers, 270M member lives covered, and $6B+ in annual cost avoidance and recoveries.
• 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.
• 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.). • Experience building or willingness to learn streaming pipelines using tools such as Kafka or SQS. • Bonus: Familiarity with healthcare data (837, 835, EHR, UB04, claims normalization).
• 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
Apply Now🕒 April 1
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