Data Analyst(SQL,Power BI) In A US Based Co

Key Responsibilities:

Dashboards and BI

• Work with Product and leadership teams to understand what they need to know, and turn that into clear metric definitions and dashboard requirements
• Explore and document our PostgreSQL data model: tables, relationships, key fields, and known data quirks
• Write efficient, well-structured SQL to pull, join, and shape data for reporting
• Build, maintain, and improve dashboards in our BI tool (Superset today), keeping them accurate, fast, and easy to use
• Define and keep a single source of truth for key metrics so numbers match across dashboards and teams
• Help migrate to a new BI tool as our stack evolves (on the short-term roadmap)

Analysis and insights

• Run ad-hoc analyses to answer business and product questions
• Track product usage, and spot trends, patterns, and anomalies in data
• Validate data quality and flag gaps or inconsistencies to engineering
• Present findings in plain language with clear, actionable recommendations

Qualifications:-

• Bachelor's degree in a core engineering discipline, mathematics, statistics, or construction management (GPA above 8 preferred)
  • Strong SQL: joins, aggregations, subqueries, CTEs, and window functions; PostgreSQL experience is a plus
  • Hands-on experience building dashboards in at least one BI tool, such as Superset, Metabase, MicroStrategy, Tableau, Power BI, Looker, or Redash (internships, projects, and coursework count)
  • Comfort learning an unfamiliar database schema and working out how the tables connect
  • Excellent Excel skills
  • Strong analytical and logical thinking, with attention to detail and accuracy
  • Clear written and verbal communication, including explaining data to non-technical people
  • Eagerness to pick up new tools quickly, since our BI stack will change
  • High ownership and comfort in a fast-moving startup
  

Good to have (not mandatory)

• Python (pandas) for analysis and automation
• Basic understanding of data modeling concepts such as fact and dimension tables, or tools like dbt
• Exposure to SaaS or B2B products
• Interest in or experience with the construction domain