Senior Data Engineer

tbc; United States; On-site; USD 150,000 - 190,000; Full time

Job summary

Lyric is a trusted leader in healthcare decision intelligence, building a data platform that ingests and serves core domains across a multi‑tenant environment. As a Senior Data Engineer on the Data Platform team, you will design and own end‑to‑end data pipelines using Airflow, dbt, and Snowflake, contributing to a canonical data model and robust quality checks.

You will collaborate with a Principal Data Engineer to shape architecture, mentor teammates, and ensure observability, scalability, and

Qualifications

• Bachelor's degree in Software Engineering, Computer Science, or a related field.
• 5+ years of experience in data engineering, building and owning production data pipelines.
• Strong Snowflake experience, including streams and tasks, warehouse sizing and performance tuning, SQL optimization, and RBAC knowledge.

Responsibilities

• Design, build, and own data pipelines in our unified framework using Airflow, dbt, and Snowflake.
• Implement the canonical data model in production, working within the architecture set by the Principal Data Engineer and contributing to it based on what implementation reveals.
• Build automated validation and data quality checks into pipelines at defined stages, so that defects are caught before they reach consumers.
• Instrument pipelines for observability, including freshness, lineage, and failure alerting.
• Contribute to self‑service capability that allows consuming teams to declare the data they need and receive it as governed output rather than a custom build.
• Partner directly with consuming teams across invoicing, analytics, and reporting to understand their requirements and translate them into data they can rely on.
• Migrate and consolidate existing data workloads onto the unified framework without disrupting the consumers depending on them.
• Participate in an on‑call rotation for pipeline and data quality incidents, and in the incident reviews that make fixes permanent.
• Hold a high engineering bar: version control, testing, code review, CI/CD, and documentation that stays current.
• Mentor engineers, share knowledge deliberately, and raise the technical level of the people around you.

Skills

Airflow

dbt

Snowflake

Python

SQL

Data modeling

RBAC

Multi‑tenant data

Education

Bachelor's degree in Software Engineering, Computer Science, or a related field

Tools

dbt

Airflow

Snowflake

Job description

Lyric is the trusted leader in healthcare decision intelligence. Built on more than 35 years of proven results, Lyric combines responsible AI with clinical, payment, regulatory, and policy expertise to deliver transparent, auditable insights in milliseconds across real-time claims workflows. Lyric augments human decision-making so health plans can make faster, more accurate payments while maintaining full control. Today, Lyric supports 200 million lives, with nine of the top 10 U.S. health plans relying on its platform to reduce waste, improve efficiency, and support accurate payments.

Applicants must already be legally authorized to work in the U.S. Visa sponsorship/sponsorship assumption and other immigration support are not available for this position.

As a Senior Data Engineer on the Data Platform team, you will build the data foundation that Lyric's products run on. Data Platform team owns the canonical data model for Lyric's core healthcare data domains, the framework that ingests, transforms, validates, and serves that data across a multi‑tenant platform, and the quality guarantees our consuming teams build against. Our stack is Snowflake, Airflow, dbt, and Python.

This is a hands‑on building role. You will design and deliver pipelines within our unified framework, implement the canonical data model in production, build validation and observability into the data path rather than around it, and help consuming teams get what they need without a bespoke build every time. You will work closely with our Principal Data Engineer, who sets architectural direction, and you will be expected to contribute to that direction.

Responsibilities

• Design, build, and own data pipelines in our unified framework using Airflow, dbt, and Snowflake.
• Implement the canonical data model in production, working within the architecture set by the Principal Data Engineer and contributing to it based on what implementation reveals.
• Build automated validation and data quality checks into pipelines at defined stages, so that defects are caught before they reach consumers.
• Instrument pipelines for observability, including freshness, lineage, and failure alerting.
• Contribute to self‑service capability that allows consuming teams to declare the data they need and receive it as governed output rather than a custom build.
• Partner directly with consuming teams across invoicing, analytics, and reporting to understand their requirements and translate them into data they can rely on.
• Migrate and consolidate existing data workloads onto the unified framework without disrupting the consumers depending on them.
• Participate in an on‑call rotation for pipeline and data quality incidents, and in the incident reviews that make fixes permanent.
• Hold a high engineering bar: version control, testing, code review, CI/CD, and documentation that stays current.
• Mentor engineers, share knowledge deliberately, and raise the technical level of the people around you.

Qualifications

• Bachelor's degree in Software Engineering, Computer Science, or a related field.
• 5+ years of experience in data engineering, building and owning production data pipelines.
• Strong Snowflake experience, including streams and tasks, warehouse sizing and performance tuning, SQL optimization, and working knowledge of RBAC, clustering, and micro‑partitions.
• Production experience with dbt and Airflow, including how to structure models and DAGs so that someone else can maintain them.
• Strong programming expertise in Python and deep SQL proficiency.
• Solid data modeling skills, with experience designing schemas that serve more than one consumer and the judgment to know when a requirement belongs in the shared model versus a consumer‑specific extension.
• Experience building testing and data quality validation into pipelines rather than checking data after the fact.
• Disciplined engineering practices: version control, code review, automated testing, and CI/CD applied as a matter of course.
• Ability to work directly with non‑engineering consumers of data, understand what they actually need, and communicate constraints and tradeoffs clearly.

Preferred

• Experience with multi‑tenant data platforms, including tenant isolation and handling per‑customer variance within a shared model.
• Experience modeling data that changes over time: event history, corrections and restatements, and the difference between point‑in‑time and as‑of reporting.
• Experience in healthcare claims, healthcare payments, or another regulated domain with PHI or PII handling and auditability requirements.
• Familiarity with Datadog or comparable observability tooling applied to data pipelines.
• Experience building internal tooling or platforms that other teams use directly.

Join our mission to drive innovation, technical excellence and global impact and contribute to the development of groundbreaking software solutions to shape the future of healthcare.

The US base salary range for this full‑time position is: $1