Data & Analytics Engineer
EXL Talent Acquisition Team- Location
- Gurugram, Haryana, India
- Workplace
- Hybrid
- Employment
- —
- Salary
- —
Posted 10d ago
- 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
- 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
Skills
- Advanced Excel
- Attention To Consistency
- Business Intelligence Tools
- Internal Communications
- Interpersonal Relationship Building
- Leadership Capabilities
- SQL Database Management
- Working under Pressure
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