Data Engineer building trusted data platforms for decision making at Lyrebird Health. Collaborating with teams to develop and maintain data pipelines and analytics-ready tables.
Responsibilities
Build end-to-end data pipelines from source systems to analytics-ready tables.
Design and maintain core data models that power product analytics, finance reporting, and dashboards.
Work with cloud data warehouses (BigQuery, Snowflake, Databricks) to deliver scalable solutions.
Use code-based transformation tools (e.g. dbt, AWS Glue) to create reliable, tested data models.
Collaborate closely with product, engineering, and business stakeholders to understand requirements and define data solutions.
Enable self-serve analytics by supporting BI tools like Looker, Sigma, and SQL-based reporting.
Contribute to CI/CD pipelines for data using GitHub and GitHub Actions.
Improve data quality, reliability, and observability as the platform scales.
Requirements
Strong fundamentals in SQL and Python.
Solid understanding of data warehousing and data modeling concepts.
Hands-on experience building pipelines on cloud data warehouses (BigQuery, Snowflake, or Databricks).
Experience with code-driven data transformation tools (dbt, AWS Glue, or similar).
Experience working with modern BI tools (Looker, Sigma, or SQL-based tools).
Comfortable using GitHub for version control and GitHub Actions for CI/CD.
Strong communication skills — able to clearly explain data concepts and trade-offs to both technical and non-technical audiences.
Stakeholder management experience — comfortable gathering requirements, aligning on definitions, and managing expectations in a fast-moving environment.
Benefits
Strong communication skills — able to clearly explain data concepts and trade-offs to both technical and non-technical audiences.
Stakeholder management experience — comfortable gathering requirements, aligning on definitions, and managing expectations in a fast-moving environment.
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