Roles & Responsibilities :
- Collaborate with product, business, and engineering stakeholders to understand key metrics, data needs, and reporting pain points.
- Design, build, and maintain clean, scalable, and reliable data models using DBT.
- Write performant SQL and Python code to transform raw data into structured marts and reporting layers.
- Create dashboards using Tableau or similar tools.
- Work closely with data platform engineers, architects, and analysts to ensure data pipelines are resilient, well-governed, and high quality.
- Define and maintain source-of-truth metrics and documentation in the analytics layer.
- Partner with product engineering teams to understand new features and ensure appropriate instrumentation and event collection.
- Drive reporting outcomes by building dashboards or working with BI teams to ensure timely delivery of insights.
- Help scale our analytics engineering practice by contributing to internal tooling, frameworks, and best practices.
Who You Are :
Experience : 2 to 3 years of experience in analytics / data engineering, with strong hands-on expertise in
DBT, SQL, Python and dashboarding tools.
Experience working with modern data stacks (e.g., Snowflake, BigQuery, Redshift, Airflow).Strong data modeling skills (dimensional, star / snowflake schema, data vault, etc.).Excellent communication and stakeholder management skills.Ability to work independently and drive business outcomes through data.Exposure to product instrumentation and working with event-driven data is a plus.Prior experience in a fast-paced, product-led company is preferred.(ref : hirist.tech)