About the role

Design and implement scalable analytical solutions and enterprise reporting structures using AWS and Power BI. Collaborate with cross-functional teams to gather requirements and ensure adherence to data governance and quality standards.

What they look for

AWS Azure Microsoft Power BI SQL Data Modeling Data Visualization ETL Data Warehousing Data Governance DAX Change Data Capture Slowly Changing Dimensions Agile Analytical Data Preparation Performance Optimization Data Schema Testing

Requirements

Requires 5-9 years of experience in analytics engineering, data modeling, and cloud ecosystems like AWS or Azure. Proficiency in SQL, Power BI, and modern data warehousing techniques is essential for this role.

Full description

Design and implement scalable analytical solutions using the AWS redshift , S3 bucket

Build and optimize transformation workflows, ingestion pipelines, and enterprise reporting structures

Develop and maintain advanced SQL scripts, views, stored procedures, and reusable analytical components

Drive enterprise-wide analytics initiatives through robust modeling and warehouse best practices along with data preparation, analytics data organization, data schema testing, and enterprise data product management.

Build and support scalable ETL workflows, ingestion pipelines, and transformation processes

Perform analytical data manipulation by writing complex SQL scripts, creating views, and optimizing queries to support reporting and business analytics needs.

Exposure with data products development, support with SCD (Slowly Changing Dimensions) ,CDC (Change Data Capture) ,Dimensional and relational modeling techniques , Enterprise warehouse frameworks

Perform detailed data quality checks, reconciliation, validation, and assessment activities

Deliver high-performing analytical solutions with strong focus on scalability, reliability, and optimization

Design and maintain analytical data models to enable scalable reporting, efficient data consumption, and business insight generation.

Develop, design, and enhance interactive dashboards and reports using Microsoft Power BI by translating client requirements into innovative BI solutions.

Participate in architecture discussions and recommend best practices for analytics modernization initiatives

Collaborate with clients, business users, and technical teams to gather analytics requirements and deliver strategic insights for decision-making.

Ensure adherence to best practices in data governance, analytical data organization, reporting standards, and cross-functional project delivery.

Candidate Profile:

5-9 years of experience with Azure/ AWS, Microsoft Power BI, SQL, analytical data modeling, data visualization, enterprise data products, and analytics engineering frameworks.

Proven experience as an Analytics Engineer with strong hands-on expertise in end-to-end modern data wareshouse build for analytical data preparation, data manipulation, schema validation/testing, and working with data products.

Strong proficiency in SQL scripting including writing complex queries, creating views, data transformation logic, performance optimization and Large-scale ingestion and transformation processes

Solid understanding of analytical data models, data modeling concepts, data organization frameworks, and enterprise analytics architecture.

Strong troubleshooting, tuning, and performance optimization capabilities

Expertise in Microsoft Power BI including dashboard development, DAX, data modeling, and advanced visualization techniques.

Good to have experience in Insurance Analytics, Financial Analytics, or strategic analytics and insights delivery for enterprise clients.

Excellent communication and stakeholder management skills with the ability to work effectively across cross-functional business and technical teams.

Exposure to modern cloud analytics ecosystems and enterprise transformation initiatives

Experience working in Agile delivery environments

Domain Expertise : Good to have

Prior experience in the Insurance domain

Good understanding of Finance processes within Insurance

Familiarity with insurance reporting, premium, claims, policy, and financial data structures is an added advantage

Responsibilities

Design and implement scalable analytical solutions using the AWS redshift , S3 bucket

Build and optimize transformation workflows, ingestion pipelines, and enterprise reporting structures

Develop and maintain advanced SQL scripts, views, stored procedures, and reusable analytical components

Drive enterprise-wide analytics initiatives through robust modeling and warehouse best practices along with data preparation, analytics data organization, data schema testing, and enterprise data product management.

Build and support scalable ETL workflows, ingestion pipelines, and transformation processes

Perform analytical data manipulation by writing complex SQL scripts, creating views, and optimizing queries to support reporting and business analytics needs.

Exposure with data products development, support with SCD (Slowly Changing Dimensions) ,CDC (Change Data Capture) ,Dimensional and relational modeling techniques , Enterprise warehouse frameworks

Perform detailed data quality checks, reconciliation, validation, and assessment activities

Deliver high-performing analytical solutions with strong focus on scalability, reliability, and optimization

Design and maintain analytical data models to enable scalable reporting, efficient data consumption, and business insight generation.

Develop, design, and enhance interactive dashboards and reports using Microsoft Power BI by translating client requirements into innovative BI solutions.

Participate in architecture discussions and recommend best practices for analytics modernization initiatives

Collaborate with clients, business users, and technical teams to gather analytics requirements and deliver strategic insights for decision-making.

Ensure adherence to best practices in data governance, analytical data organization, reporting standards, and cross-functional project delivery.

Qualifications