Data & Analytics Engineer

• 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

1. Prior experience in the Insurance domain 
2. Good understanding of Finance processes within Insurance 
3. Familiarity with insurance reporting, premium, claims, policy, and financial data structures is an added advantage 

• 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

1. Prior experience in the Insurance domain 
2. Good understanding of Finance processes within Insurance 
3. Familiarity with insurance reporting, premium, claims, policy, and financial data structures is an added advantage