Job description
Machinify is the leading provider of AI-powered software products that transform healthcare claims and payment operations. Each year, the healthcare industry generates over $200B in claims mispayments, creating incredible waste, friction and frustration for all participants: patients, providers, and especially payers. Machinify’s revolutionary AI-platform has enabled the company to develop and deploy, at light speed, industry-specific products that increase the speed and accuracy of claims processing by orders of magnitude.
Why this role matters
As a Data Engineering Manager, you will lead a high-performing team responsible for transforming raw external and customer data into actionable, trusted datasets. Your team’s work powers product decisions, ML models, operational dashboards, and client integrations.
You’ll combine hands-on technical expertise with people and project leadership, reviewing and designing production pipelines, mentoring engineers, and driving best practices. You will also be a key cross-functional partner, collaborating with product managers, Server teams, Platform teams, UI teams, SMEs, account managers, analytics teams, ML/DS teams, and customer success to ensure data is accurate, reliable, and impactful.
This is a high-visibility role with both strategic and tactical impact — shaping data workflows, onboarding new customers, and scaling the team as the company grows.
What You’ll Do
Lead, mentor, and grow a high-performing team of Data Engineers, fostering technical excellence, collaboration, and career growth.
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.
Collaborate with senior leadership to define team priorities, project roadmaps, and data standards, translating objectives into actionable assignments for your team.
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.
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.
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.
Measure team impact through metrics and KPIs, ensuring alignment with company goals.
What You Bring
Degree in Computer Science, Engineering, or a related field.
3+ years of combined technical leadership and engineering management experience, preferably in a startup, with a proven track record of managing data teams and delivering high-impact projects from concept to deployment.
10+ years of experience in data engineering, including building and maintaining production pipelines and distributed computing frameworks.
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.
Exceptional ability to manage priorities, communicate clearly, and work cross-functionally, with experience building and leading high-performing teams.
Demonstrated experience leading small teams, including performance management and career development.
Comfortable with ambiguity, taking initiative, thinking strategically, and executing methodically.
Ability to drive change, inspire distributed teams, and solve complex problems with a data-driven mindset.
Customer-oriented, ensuring work significantly advances product value and impact.
Bonus:
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.
Why you’ll love working here
High Impact: Your team’s work powers key decisions across product, ML, operations, and customer-facing initiatives.
Ownership & Growth: Influence the data platform and pipeline architecture while mentoring a growing team.
Cross-Functional Exposure: Work with product, platform, engineering , ML, analytics, and customer teams to solve meaningful problems.
Remote Flexibility: Fully remote with opportunities to collaborate across teams.
Early Builder Advantage: Shape processes, standards, and practices as we scale.
Equal Employment Opportunity at Machinify
Machinify is committed to hiring talented and qualified individuals with diverse backgrounds for all of its positions. Machinify believes that the gathering and celebration of unique backgrounds, qualities, and cultures enriches the workplace.
See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/
