Lead Data Engineer
Gifthealth Inc Columbus, Ohio, United States · $150K–$170K/yr
Technology, Information and Internet · 1,001-5,000 employees
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About the role
The Lead Data Engineer will own domains of the data platform, setting technical direction and managing a team of senior and mid-level engineers. They are responsible for developing roadmaps, establishing engineering standards, and ensuring the accuracy and timeliness of client data feeds.
What they look for
Requirements
Candidates must have 7 to 10 years of data engineering experience, including production ownership of a cloud data warehouse and at least one year of people management. A bachelor's degree in a technical field or equivalent work experience is required, along with expertise in SQL, Python, and dbt.
Full description
Description
Lead Data Engineer
About Us
At Gifthealth, we're revolutionizing the way people experience healthcare by simplifying the
process of managing prescriptions and health services. Our mission is to provide a seamless,
personalized, and efficient healthcare experience for all our customers. We're a dynamic,
innovative, and customer-centric company dedicated to making a positive impact on people's
lives.
Position Summary
We are seeking a Lead Data Engineer to own one or more domains of the data platform,
set their long-term technical direction, and manage a team of senior and mid-level data
engineers. This position plays a key role in supporting the Data Engineering department and
reports to the Manager, Data Engineering, ensuring alignment with organizational goals,
operational excellence, and compliance standards.
Key Responsibilities
? Own one or more domains of the data platform on a continuing basis. The initial
assignment is expected to be ingestion and orchestration, including the transition off the
current managed ingestion platform, replacement connectors, scheduling, and the
interface between raw data and the dbt layer. Other potential domains include the
transformation layer and client-facing data feeds.
? Set technical direction for assigned domains, including source onboarding, incremental
modeling standards, and decisions on when to rebuild existing pipelines. Document
designs prior to development and serve as the final reviewer for domain work.
? Develop and maintain a 12 to 18 month roadmap for each assigned domain, subject to
approval by Data & Analytics leadership.
? Establish engineering standards and code review practices for assigned domains for
adoption across the Data Engineering team.
? Manage the domain backlog, set priorities, and allocate team capacity across
stakeholder requests.
? Ensure the accuracy and timeliness of scheduled client data feeds to manufacturers by
building and maintaining testing, monitoring, and reconciliation processes.
? Track and report domain performance to Data, Analytics & AI leadership, including feed
timeliness, data accuracy, incident volume, and operating cost.
? Lead incident response for assigned domains, including escalation, post-incident
reviews, and corrective actions.
? Design and implement a data quality framework for assigned domains, which includes
validation rules, automated testing, monitoring & alerting, and report data quality metrics
to stakeholders.
? Design and maintain data access controls that meet HIPAA and BAA requirements,
including masking policies and role-based access.
? Manage two to three senior and mid-level data engineers, with responsibility for hiring,
onboarding, goal setting, performance reviews, compensation recommendations, and
performance management. Approximately 65% of time is expected to be hands-on
technical work.
? Develop budget recommendations for domain tooling and infrastructure, such as
ingestion connectors and Snowflake compute. Lead vendor evaluations (e.g.,
replacement of the current managed ingestion platform) and present recommendations
to the Director, Data, Analytics & AI for approval.
? Serve as the primary point of contact for assigned domains with product, engineering,
pharmacy operations, compliance, and account management teams.
? Contribute to the entity-resolution layer that matches patient and provider identities
across a variety of source systems.
Qualifications
? Education: Bachelor's degree (BA/BS) in Computer Science, Data Science, Information
Systems, Software Engineering, Mathematics, Statistics, or a related field, or
comparable work experience.
? Licensure/Certification: Not applicable to this role.
? Experience: 7 to 10 years of data engineering experience, including production
ownership of a cloud data warehouse (Snowflake preferred) and at least one year of
direct people management experience.
? Knowledge, Skills, and Abilities:
? Required:
¦ Production ownership of a cloud data warehouse; Snowflake experience
preferred.
¦ Expert-level SQL and proficiency in Python, including the ability to
troubleshoot complex SQL and dbt models.
¦ Experience with dbt at scale, including incremental models, testing, CI,
and project structure.
¦ Production experience with an orchestration tool such as Airflow, Dagster,
or Prefect.
¦ Experience owning a platform area or major system over multiple years,
including setting its direction and accountability for results.
¦ At least one year of direct people management experience, including
hiring, performance reviews, and developing engineers at multiple levels.
¦ Experience implementing automated data quality testing and alerting.
¦ Ability to communicate data issues, business impact, and resolution
timelines to client-facing teams.
¦ Working knowledge of healthcare data, PHI, and HIPAA requirements.
¦ Demonstrated ability to lead a team and set technical direction for a
domain.
¦ Experience developing technical roadmaps and making build-versus-buy
and vendor recommendations supported by cost analysis.
¦ Strong leadership, communication, and decision-making skills.
? Preferred:
¦ Experience with healthcare, pharmacy, or other regulated data, including
PHI, HIPAA, and BAAs.
¦ Experience with large-scale data platform migrations.
¦ Experience with infrastructure as code, particularly Terraform.
¦ Experience with identity resolution or master data management.
¦ Experience building custom ingestion connectors.
¦ Familiarity with Looker and LookML. Looker is the primary BI platform at
Gifthealth, with Metabase also in use and Domo being retired.
Work Environment
? Location: Columbus, OH or remote (US).
? Schedule: Full-time.
? On-call availability may be required to support scheduled client data feeds.
? Regular meetings with the Data Engineering team, direct reports, and Data, Analytics &
AI leadership.
Key Essential Functions
? Not applicable. This is a standard office/remote engineering role with no physical labor
requirements.
? Periodic on-site visits to the Columbus distribution center and call center are expected,
primarily during onboarding.
Employment Classification
Status: Full-time
FLSA: Exempt
Equal Employment Opportunity (EEO) Statement
Gifthealth is an Equal Opportunity Employer and prohibits discrimination and harassment of any
kind. All employment decisions are made without regard to race, color, religion, sex, sexual
orientation, gender identity, transgender status, national origin, age, disability, veteran status, or
any other legally protected status.
We celebrate diversity and are committed to creating an inclusive environment for all
employees. If you do not meet every requirement but still feel you would be a great fit for this
role, we encourage you to apply!
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