About The Role

The Business Data Analyst turns operational and product data into reliable reporting, actionable insights, and decision-ready analysis. The role works across SQL-based data warehouses, dbt models, and BI tools to define metrics, investigate performance changes, and improve visibility into business health.

The analyst partners with product, operations, finance, and engineering teams to translate ambiguous questions into structured analyses and repeatable dashboards. This work matters because accurate definitions, trusted pipelines, and clear reporting directly influence prioritization, forecasting, and customer outcomes.

Key Responsibilities

Build and maintain analytical datasets and reporting models using SQL, dbt, and a cloud data warehouse such as Snowflake, BigQuery, or Redshift
Create and manage dashboards in Looker, Tableau, or Power BI, including metric definitions, drill-downs, alerts, and documentation
Analyze product, customer, and operational data to identify trends, anomalies, drivers of performance, and opportunities for improvement
Partner with stakeholders to define business requirements, establish trusted KPIs, and deliver recurring reporting with clear recommendations
Validate data quality across source systems and transformation layers; investigate discrepancies and coordinate fixes with data engineering
Automate recurring analyses and reporting workflows using Python, SQL, spreadsheets, or BI platform capabilities
Present findings to technical and non-technical audiences through concise written analysis, visualizations, and executive-ready summaries

What We Are Looking For

1–3 years of experience in business analytics, data analysis, product analytics, operations analytics, or a related role
Strong SQL skills, including joins, CTEs, window functions, aggregations, and query optimization against large datasets
Hands-on experience with at least one BI platform such as Looker, Tableau, or Power BI, including dashboard development and semantic metric design
Working knowledge of modern data transformation practices and tools such as dbt, version control, data testing, and dimensional modeling
Experience using Python or a comparable scripting language for analysis, data validation, or workflow automation
Bachelor’s degree in analytics, statistics, economics, computer science, business, or a related quantitative field, or equivalent practical experience
Bonus: Experience with Snowflake, BigQuery, Redshift, Amplitude, Segment, experimentation analysis, forecasting, or product-led technology environments

Job description