Data Engineering Manager
SmarterDx · United States
- Hybrid
- Full-time
- $210,000 / year
- United States
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Job highlights
- Lead data engineering team for healthcare data integration.
- Ensure high data quality and governance standards.
- Manage and optimize ELT pipelines using modern tools.
- Drive client onboarding speed through automation.
- Collaborate cross-functionally for product delivery.
About the role
Data Engineering Manager
SmarterDx is seeking a Manager of Data Engineering, Integrations to lead and grow a high‑performing data engineering team responsible for ingesting, harmonizing, and operationalizing healthcare data (EHR, clinical, and claims) across our products. You will scale new‑client onboarding, raise the bar on data quality and governance, and ensure resilient, observable, and cost‑effective ELT pipelines. You will set clear objectives, mentor engineers, and partner closely with Product, Clinical, Data Science, and Engineering to deliver durable outcomes.
SmarterDx builds clinical AI that empowers hospitals to analyze the complete record of every patient to fully capture the value of care delivered. Founded by physicians in 2020, its proprietary AI platform understands the nuances of clinical reasoning, enabling hospitals to true the patient record for every discharge. By doing so, hospitals can recover millions in earned revenue, enhance care quality metrics, and optimize healthcare operations. Become a Smartian and help optimize the way the healthcare system works for everyone. Learn more at smarterdx.com/careers.
What You'll Do
- Lead, coach, and develop a team of analytics engineers and/or data engineers with a focus on technical excellence, delivery velocity, and collaborative culture.
- Ensure on-time delivery of client data integrations by owning enterprise data model standards and maintaining consistent, governed data definitions.
- Oversee client data pipelines using modern tooling (dbt, Airflow, Snowflake, AWS, Python) to ensure reliable operation and uptime.
- Drive client integration delivery speed by implementing automation, reusable patterns, and clear runbooks to directly optimize client onboarding timelines.
- Establish and enforce SLOs/SLAs, instrument critical paths, and drive incident reduction via proactive monitoring, alerting, and post‑incident reviews.
- Implement comprehensive data quality and testing frameworks (schema, nullability, referential integrity, lineage observability).
- Collaborate cross‑functionally (Product, Clinical, Data Science, Engineering) to prioritize roadmaps, land measurable outcomes, and manage tradeoffs.
- Manage high-volume client integration requests, triaging and prioritizing tickets based on client impact, urgency, and business value while maintaining clear communication on resolution timelines.
- Own daily operations rhythm including ticket review, resource allocation, escalation management, and stakeholder updates to ensure client integration commitments are met.
- Drive operational metrics and reporting on integration delivery performance, ticket resolution times, and team capacity to identify bottlenecks and improve client outcomes.
What You Bring
- 7+ years of data engineering experience, including leadership of engineers and outcomes (hiring, mentoring, performance, delivery).
- Deep experience with healthcare datasets: clinical, and/or billing/claims; familiarity with HL7/FHIR and interoperability patterns.
- Strong SQL and data modeling expertise; proven track record building reliable ELT in dbt, Airflow, Snowflake, and Python.
- An Operational excellence mindset that integrates SLOs/SLAs, on‑call/incident management, root‑cause analysis, and preventive improvements.
- Demonstrated ability to accelerate client data onboarding through automation, standardization, and repeatable integration patterns.
- Excellent communication and stakeholder management; comfortable driving clarity and alignment across Product, Clinical, and technical partners.
- Willingness to roll up sleeves and contribute hands‑on to unblock the team.
Nice To Haves
- Experience at a scale‑up or rapid‑growth technology company.
- Experience leading product implementations and complex client data integrations.
- Hands‑on interoperability experience (HL7, FHIR, CCD/C-CDA), EHR extract patterns, and healthcare data normalization.
- Certifications: Snowflake (SnowPro), AWS (Data Analytics or Solutions Architect), dbt, or healthcare data (CHDA/RHIA).
Our Tech Stack
- Databases: Snowflake (primary), Postgres
- Cloud Infrastructure: AWS (CDK, S3, MWAA, EventBridge, Batch, Lambda, Step Functions)
- Technologies: SQL, dbt, Airflow, Python, FiveTran
Compensation
$190,000 - $210,000
Benefits
- Medical, Dental & Vision – Comprehensive plans with leading insurance providers, covering 75% of your premiums, depending on the plan.
- Paid Parental Leave – Generous paid leave to support families through birth or adoption: Up to 12 weeks for parents.
- Remote-First Team – Work from anywhere in the U.S.
- Unlimited PTO & 10 Holidays – So you can relax and recharge.
- 401(k) with Traditional & Roth Options – Tax-advantaged retirement savings through Fidelity with a 4% match.
- Minimal Bureaucracy – A fast-moving, high-impact environment where you can focus on what matters.
- Incredible Teammates! – Work alongside smart, supportive, and mission-driven colleagues.
Key skills/competency
- Data Engineering Manager
- Healthcare Data
- ELT Pipelines
- Data Quality
- Data Governance
- SQL
- dbt
- Airflow
- Snowflake
- AWS
Skills & topics
- Data Engineering Manager
- Healthcare Data
- ELT
- Data Quality
- Data Governance
- SQL
- dbt
- Airflow
- Snowflake
- AWS
- Python
- Clinical AI
- Health Tech
- Remote
How to get hired
- Tailor your resume: Highlight your 7+ years of data engineering experience, leadership, and healthcare data expertise. Emphasize your success with ELT pipelines, SQL, dbt, Airflow, Snowflake, and AWS.
- Showcase healthcare domain knowledge: Detail your familiarity with clinical, claims, HL7/FHIR, and interoperability patterns. Quantify achievements in improving data quality and client onboarding.
- Demonstrate operational excellence: Provide examples of implementing SLOs/SLAs, incident management, and automation for data integration.
- Prepare for technical and behavioral interviews: Be ready to discuss your leadership approach, technical problem-solving skills, and experience managing cross-functional stakeholders.
- Research SmarterDx: Understand their mission to transform healthcare payment through clinical AI and their remote-first culture.
Technical preparation
Master SQL for complex data manipulation.,Practice dbt for data transformation.,Familiarize with Airflow for orchestration.,Review AWS services for data pipelines.
Behavioral questions
Describe a challenging team leadership experience.,How do you ensure data quality under pressure?,Share an experience driving cross-functional alignment.,How would you handle an integration incident?
Frequently asked questions
- What is the primary focus of the Data Engineering Manager role at SmarterDx?
- The Data Engineering Manager at SmarterDx will lead a team focused on ingesting, harmonizing, and operationalizing healthcare data (EHR, clinical, claims) to support their clinical AI platform. Key responsibilities include scaling client onboarding, enhancing data quality and governance, and ensuring robust ELT pipelines.
- What are the essential technical skills required for the Data Engineering Manager at SmarterDx?
- Essential technical skills include 7+ years of data engineering experience, deep knowledge of healthcare datasets (clinical, claims), strong SQL and data modeling, and proven experience with ELT tools like dbt, Airflow, Snowflake, and Python. Experience with AWS cloud infrastructure is also critical.
- What is the work arrangement for the Data Engineering Manager position at SmarterDx?
- This is a fully remote position within the United States. SmarterDx operates as a remote-first company, offering flexibility for employees to work from anywhere in the U.S.
- How does SmarterDx approach data quality and governance in this role?
- The role emphasizes raising the bar on data quality and governance. This involves establishing and enforcing SLOs/SLAs, implementing comprehensive data quality and testing frameworks, and ensuring lineage observability for all data pipelines.
- What opportunities are there for professional growth as a Data Engineering Manager at SmarterDx?
- As a manager, you'll have the opportunity to lead, coach, and develop a team of engineers, fostering technical excellence and a collaborative culture. You'll also play a key role in shaping the data infrastructure of a growing company in the impactful health-tech sector.
- What specific healthcare data formats does SmarterDx work with?
- SmarterDx works with various healthcare datasets including EHR, clinical, and claims data. Familiarity with interoperability standards like HL7/FHIR is highly valued, along with experience in healthcare data normalization.
- How does SmarterDx handle client integrations and onboarding?
- The role is responsible for scaling new-client onboarding and driving integration delivery speed. This is achieved through implementing automation, reusable patterns, clear runbooks, and managing high-volume integration requests efficiently.
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