𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟱𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟴𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟱-𝟴 𝗟𝗣𝗔)

Experience: 3+ yrs

Location: Vadodara, Gujarat, India

Job Type: Full-time

We are looking for an experienced Business Intelligence Engineer to help build and scale enterprise data and analytics capabilities. The role combines business intelligence, analytics engineering, data modelling, reporting, and data platform development, with a strong focus on transforming raw operational data into trusted, analytics-ready datasets and business insights.

The ideal candidate will have strong expertise in Power BI, SQL, Snowflake, and dbt, along with a solid understanding of modern data warehousing, semantic modelling, data quality, and governance.

Requirements

Key Responsibilities

• Develop and maintain Power BI semantic models, datasets, dashboards, and reports for enterprise reporting and analytics.
• Partner with business stakeholders and data teams to understand reporting requirements and translate business questions into scalable data solutions.
• Build reusable data products and analytics solutions aligned with business objectives.
• Develop and maintain SQL queries, data transformations, and analytics-ready datasets.
• Support ELT workflows and data processing pipelines across enterprise data platforms.
• Develop and maintain dbt models, transformations, tests, and documentation.
• Design dimensional models, star schemas, semantic layers, and data warehouse structures.
• Work with Snowflake to develop, optimise, and maintain analytics-ready data models.
• Support onboarding and integration of new data sources into the enterprise data platform.
• Implement data validation, quality checks, reconciliation, monitoring, and troubleshooting processes.
• Investigate and resolve data discrepancies, reporting issues, and data-quality problems.
• Contribute to KPI standardisation, metric definitions, metadata management, data lineage, and reporting governance.
• Optimise Power BI and Snowflake solutions for performance, scalability, usability, and cost efficiency.
• Collaborate with Data Engineers, Analytics Engineers, Data Analysts, and external technology partners.
• Identify opportunities to automate manual reporting and data preparation activities.
• Contribute to source control, deployment, and CI/CD practices for analytics development.
• Maintain technical documentation and promote consistent enterprise reporting standards.
• Stay current with emerging capabilities across Power BI, Snowflake, dbt, cloud data platforms, and modern analytics engineering.

What Makes You a Great Fit

• 3–7 years of experience in Business Intelligence, Analytics Engineering, Data Engineering, or a related discipline.
• Strong hands-on expertise in Power BI, including semantic models, datasets, dashboards, and enterprise reporting.
• Strong SQL development and data transformation skills.
• Hands-on experience with Snowflake or a comparable cloud data warehouse.
• Practical experience developing and maintaining dbt models, transformations, testing, and documentation.
• Strong understanding of dimensional modelling, star schemas, data warehousing, and semantic layers.
• Experience troubleshooting data-quality, reporting, data pipeline, and performance issues.
• Familiarity with Git, Azure DevOps, source control, and modern development workflows.
• Understanding of data governance, metadata, lineage, documentation, and enterprise reporting standards.
• Experience with Azure-based data platforms is an advantage.
• Familiarity with Python for data analysis, automation, or data engineering is preferred.
• Experience supporting enterprise reporting environments with large user populations is a plus.
• Knowledge of CI/CD practices for analytics and data development is advantageous.
• Experience with construction, real estate, manufacturing, or operational analytics will be beneficial.
• Strong analytical, problem-solving, and attention-to-detail skills.
• Excellent written and verbal English communication skills.
• Ability to collaborate effectively with technical teams and business stakeholders.