Data Anlytice

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.

- Solid 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 patterns.

- Strong understanding of data lineage, metadata traceability, and impact analysis.

- Experience applying governance-by-design and data observability (data quality tests, lineage, and certified datasets).

- Effective communication skills with ability to work directly with business stakeholders.

- Excellent analytical and problem-solving skills.

Education / Professional Experience/ Qualifications

- Bachelor of Science (BS) in Computer Science, Information Systems, Analytics, or related field (or equivalent work experience).

- 5+ years of analytics engineering, BI/data warehouse development, or related data experience in enterprise data environments.

- Preferred: Experience in professional services, accounting industry, or client service/consultative technology roles.

- Experience with ETL/ELT tools (Informatica, dbt).

- Experience with BI/reporting tools (Power BI, Tableau, Excel).

- Experience with data modeling methodologies (Dimensional modeling, Data Marts, Data Warehousing, Star/Snowflake schema).

- Familiarity with cloud data platforms (Azure, AWS, GCP).

- Agile/Scrum delivery exposure.

📌 Immediate Hiring For Data Analytics Engineer - Hyderabad
🏢 Grant Thornton
📍 Hyderabad