Analytics Engineer

5 days ago

Vadodara, Gujarat, India Hexpress Healthcare Full time ₹ 9,00,000 - ₹ 12,00,000 per year

We are seeking a proactive and skilled Analytics Engineer to join our Data team. This mid-level role is crucial for bridging the gap between raw data and actionable business insights. You will be responsible for designing, developing, and maintaining scalable and reliable data models that empower our Analysts, Data Scientists, and business stakeholders to make data-driven decisions. The ideal candidate has a strong background in data warehousing, advanced SQL, and modern data transformation tools.

Key Responsibilities:

  • Data Modelling & Transformation (ELT):

  • Design, develop, and implement production-ready data models (e.g., dimensional modelling) within the cloud data warehouse.

  • Develop, test, and maintain robust data transformation logic using dbt (data build tool) and SQL to clean, enrich, and standardise raw data.

  • Ensure data definitions, metrics, and business logic are consistent and accurately applied across all data models.

  • Business Dashboards:

  • Design and optimise reporting tables/marts specifically to support core business dashboards in tools like Looker or Power BI.

  • Ensure that the underlying data models are highly performant for BI tool queries (e.g., proper aggregation, indexing, and partitioning to minimise query run time).

  • Develop semantic layer definitions (e.g., LookML in Looker, calculated fields in Power BI) to define and standardise key business metrics for self-service analysis.

  • Business Intelligence:

  • Serve as a key link between business stakeholders and the data platform, translating vague business questions into measurable metrics, clear analytical requirements, and data model designs.

  • Conduct exploratory data analysis on structured data sets to uncover trends, root causes for business performance changes, and new insights that drive strategic decisions.

  • Provide training and support to internal business users (e.g., Marketing, Finance, Product teams) on how to effectively use the standardised BI tools and data models for their own self-service analysis.

  • Data Quality & Governance:

  • Implement automated data quality checks and monitoring within the ELT process to ensure data integrity and reliability.

  • Maintain clear and comprehensive documentation for data models, business logic, and lineage.

  • Collaborate with Data Governance teams to ensure compliance and security standards are met.

  • Pipeline Support:

  • Work closely with Data Engineers to ensure efficient data ingestion and flow into the data warehouse.

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