Senior Data Analyst: Pipelines & AI-Driven Insights (Remote)

Crystal Equation Corporation; California (MO); Hybrid; USD 88,000 - 95,000; Full time

Benefits offered by this job

Full benefits

Time off

401K

Job summary

Crystal Equation is seeking a Business Systems Analyst III for remote work in the United States. The role emphasizes owning and improving Enterprise Support data systems, data pipelines, and dashboards, with opportunities to apply AI/LLM tooling and propose better data models.

Candidates should have 6-7 years in data analytics, strong SQL (Presto/Hive), data modeling, and reporting skills. Responsibilities include governance, backfills, and building scalable data solutions across the enterprise.

Responsibilities

• Own the day to day health of the Enterprise Support data layer: pipelines, Hive tables, SQL, and dashboards
• Design and build data models for new reporting needs, proposing the approach rather than receiving a specification
• Maintain a documented source of truth for Enterprise Support metrics: definitions, ownership, and freshness
• Apply AI and LLM tooling to accelerate data work and to extract signal from unstructured support data such as ticket notes and resolution summaries
• Improve pipeline reliability and reduce manual effort over time through automation
• Monitor pipeline health, resolve failures and data quality issues, and run backfills
• Deliver recurring reporting (weekly, monthly, quarterly) and ad hoc analysis
• Apply and maintain standards for naming, documentation, and schema change management
• Proactively surface data quality, governance, and coverage gaps

Job description

Crystal Equation is seeking a Business Systems Analyst III for remote work in the United States. The role emphasizes owning and improving Enterprise Support data systems, data pipelines, and dashboards, with opportunities to apply AI/LLM tooling and propose better data models.

Candidates should have 6-7 years in data analytics, strong SQL (Presto/Hive), data modeling, and reporting skills. Responsibilities include governance, backfills, and building scalable data solutions across the enterprise.