Want to know if this job is worth applying to?
United States
Remote only
About the Role:
We are looking for an exceptional Sr. Data Engineer to join our team and help shape the future of mental health care. We care deeply about making a difference in people's lives, and we hope that you do too!
At Lyra Health, data is not just a byproduct of the business, it powers the analytics and research platforms that drive product development and measure life-changing clinical outcomes. As a critical pillar of Lyra's data strategy, you will build and scale our data enterprise that empowers our teams to make better decisions and our patients to live happier, healthier lives.
To thrive in this role, you should be enthusiastic about taking ownership of your work, spearheading cross-functional projects, and providing guidance and mentorship to other members of the team
Lyra is the right place for you if you:
Join a team of innovative engineers building and scaling the core data infrastructure, pipelines, and services that power our products
Design and implement a robust data warehouse to support a wide range of analytics and operational use cases
Develop and maintain efficient data pipelines and curated data sets by working closely with stakeholders to gather requirements and translate them into technical solutions
And of course—write code every day!
4+ years of experience as a Data Engineer.
Proven track record of writing high-quality, production-ready Python and delivering impactful, scalable data projects.
Expertise in SQL-based data modeling and transformation frameworks (e.g. dbt), with a focus on schema management, performance, and data governance.
Strong experience with modern ingestion tools: configuring, deploying on data integration platforms (e.g. Airbyte), commercial ELT pipelines (e.g. Fivetran), and database replication methods like Change Data Capture (CDC).
Strong orchestration background: hands-on experience building robust, fault-tolerant pipelines using Apache Airflow (including custom alerting, advanced logging, and automated retry mechanisms).
Experience with modern data visualization and analytics tools such as Sigma or Tableau.
Strong knowledge of Snowflake Cloud Data Warehouse Architecture, including native ingestion patterns (e.g. Snowpipe for continuous streaming) and open table formats (e.g. Apache Iceberg).
Strong knowledge of Snowflake administration including familiarity with maintaining security compliance, role based access control (RBAC), external authentication methods, and managing downstream data consumption in external platforms.
A "QA-First" engineering mindset: Strong experience in end-to-end data quality assurance, regression testing, and data validation. Capable of troubleshooting data discrepancies, and performance-tuning complex pipelines.
Strong foundational knowledge of relational databases, core data warehousing principles, and dimensional modeling techniques.
Experience working with sensitive data (such as PII/PHI) within healthcare or similarly regulated environments, implementing robust data masking or redaction processes.
Familiarity with DevOps principles and infrastructure automation using Terraform.
A thoughtful approach to balancing high-quality engineering standards with tight deadlines.
Excellent communication skills with a talent for building consensus and distilling complex technical problems into clear, actionable business priorities.