Job Summary

Grant Thornton GTech's Data Analytics function is dedicated to designing and delivering robust global data platforms that enable business solutions and high-quality analytics. The Analytics Engineer is responsible for building curated, analytics-ready datasets and semantic models that bridge data engineering and analytics, enabling trusted reporting and self-service consumption within the organization's Data Lakehouse. This hands-on role focuses on transformation development (dbt), dimensional modeling, semantic-layer and BI delivery (Power BI), and data quality. Working closely with Business teams, Data Architects, Data Engineers, and Analysts, the Analytics Engineer turns business requirements into well-structured, governed, and performant data products that serve as a trusted foundation for analytics, reporting, and AI.

Responsibilities

- Design, build, and maintain curated, analytics-ready (gold-layer) datasets and semantic models that enable trusted reporting and self-service consumption.
- Develop and maintain modular, well-documented data transformations using dbt, following established engineering standards and reusable patterns.
- Build and optimize dimensional models (star/snowflake schemas, data marts) aligned with the Medallion architecture (Bronze/Silver/Gold layer separation).
- Develop semantic models, metric definitions, and certified datasets in Snowflake and Power BI to support consistent, governed analytics consumption.
- Translate business and reporting requirements into transformation logic and business rules in partnership with data analysts and stakeholders.
- Conduct data profiling, validation, and reconciliation using Snowflake SQL to ensure the accuracy, completeness, and integrity of analytics outputs.
- Perform data lineage and impact analysis across Snowflake, upstream sources,



transformation layers, and reporting layers.
- Implement data quality checks, tests, and observability for analytics pipelines and datasets.
- Optimize Snowflake queries, models, and transformations for performance, reliability, and cost efficiency.
- Collaborate with data engineers, ETL/ELT developers, and QA, and support UAT to resolve data-related gaps through iterative testing and validation.
- Apply governance-by-design practices (access, classification/metadata, certified datasets), and mentor and guide more junior team members.

Skills

- Proven experience with Machine Learning, predictive analytics, and natural language processing.
- Strong programming skills in SQL and Python for data validation, profiling, reconciliation, and analytics.
- Strong hands-on Snowflake experience is required, including, ability to construct optimize complex SQL queries, variant/JSON parsing, schema and stage understanding, performance analysis troubleshooting, dynamic tables/materialized views, dbt-on-Snowflake (Streams Tasks), and secure views/masking for certified datasets.
- Working experience in Medallion Architecture (Bronze, Silver, Gold data layers) including mapping data flows across layers.
- Robust hands-on experience with dbt for building and maintaining modular, tested data transformations (ELT/ETL development and maintenance).
- Hands-on experience building semantic models and reports in Power BI (metric definitions, certified datasets, and self-service enablement).
- Experience developing curated, analytics-ready (gold-layer) datasets and reusable transformation

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Data Analytics Engineer (Senior Associate) (Bengaluru)
🏢 Grant Thornton
📍 Bengaluru