Machinify is looking to solve the business problem of over $200B in annual healthcare claims mispayments by transforming healthcare claims and payment operations with AI-powered software. The Data Engineering Manager will lead a team to turn raw data into actionable datasets that power product decisions, ML models, and operational dashboards.
Requirements
- Strong expertise in Python, Spark, SQL, and Airflow
- Hands-on experience in pipeline architecture, code review, and mentoring junior engineers.
- Prior experience with customer data onboarding and standardizing non-canonical external data.
- Deep understanding of distributed data processing, pipeline orchestration, and performance tuning.
- Familiarity with healthcare data (837/835 claims, EHR, UB04).
- Experience with cloud platforms (AWS/GCP), databricks, streaming frameworks (Kafka/SQS), and containerized workflows (Docker/Kubernetes).
- Experience building internal DE tooling, frameworks, or SDKs to improve team productivity.
Responsibilities
- Own the design, review, and optimization of production pipelines, ensuring high performance, reliability, and maintainability.
- Drive customer data onboarding projects, standardizing external feeds into canonical models.
- Ensure high data quality, observability, and automated validations across all pipelines.
- Contribute hands-on when necessary to architecture, code reviews, and pipeline design.
- Identify and implement tools, templates, and best practices that improve team productivity and reduce duplication.
- Lead sprint planning and work with cross-functional stakeholders to prioritize initiatives that improve customer metrics and product impact.
- Partner closely with Product, ML, Analytics, Engineering, and Customer teams to translate business needs into effective data solutions.
Other
- Lead, mentor, and grow a high-performing team of Data Engineers, fostering technical excellence, collaboration, and career growth.
- Collaborate with senior leadership to define team priorities, project roadmaps, and data standards, translating objectives into actionable assignments for your team.
- Build cross-functional relationships to advocate for data-driven decision-making and solve complex business problems.
- Hire, mentor, and develop team members, fostering a culture of innovation, collaboration, and continuous improvement.
- Communicate technical concepts and strategies effectively to both technical and non-technical stakeholders.
