Note: The job is a remote job and is open to candidates in USA. ClubReady is the operating platform for boutique fitness, supporting a large portfolio of franchise fitness operators. The Senior Data Engineer will design and maintain data solutions, manage the customer-facing data mart, and collaborate with teams to enhance data processes and reporting capabilities.
Responsibilities
- Design, optimize, and maintain stored procedures and SSRS reports across the ClubReady reporting environment
- Own the customer-facing Postgres data mart product serving enterprise clients
- Co-own migrating from the legacy Go ETL to the new Fivetran → Snowflake → dbt → Postgres pipeline, partnering with the central data team
- Serve as technical domain expert for assisting data mart customers
- Triage and resolve customer-reported data discrepancies
- Author Azure DevOps work items, review pull requests, and operate inside two-week sprints
- Maintain the internal data dictionary and the external data documentation
- Tune queries and indexes against very large tables (multi-billion-row scale) where wrong choices have real customer-visible cost
- Join customer calls directly with enterprise account managers and customer-side data analysts to scope and deliver work
Skills
- 5+ years of data engineering or BI development experience with deep T-SQL and SQL Server in a transactional, customer-facing environment
- Bachelor's degree in Computer Science, Information Systems, Engineering, or related field — or equivalent professional experience
- Production experience with at least one analytics warehouse stack (Snowflake, BigQuery, or Redshift) and modern ELT tooling (dbt, Fivetran, Airbyte, or similar)
- Strong query performance instincts: indexing strategy, execution plans, statistics, partitioning, and rewrite patterns for legacy procs
- Proficiency in SQL and at least one scripting language (Python preferred)
- Experience with SSRS or another enterprise reporting platform
- Demonstrated ability to operate as a senior IC: own scope end-to-end without close supervision
- Excellent written and verbal communication
- Comfort working directly with external customers and stakeholders (finance teams, account managers, customer-side analysts)
- Experience supporting a multi-tenant data product (per-customer schemas, row-level security, tenant onboarding workflows)
- Postgres at production scale
- Experience within the boutique fitness industry
- Go experience for maintaining the legacy custom ETL during the sunset period
- Familiarity with Azure DevOps for source control and work tracking
- Exposure to AI-assisted analytics work (Snowflake Cortex, Claude, embedded LLM reporting)
- Track record of mentoring or growing more junior engineers
Company Overview