Team Member - Data Warehouse

Skillventory; Navi Mumbai, Mumbai; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Skillventory is seeking a seasoned Data Engineering professional to support and advance the Enterprise Data Warehouse and Information Management roadmap in Navi Mumbai. The role involves data modernization, platform enhancements, and automation across cloud, big data, and enterprise platforms.

You will design, develop, and maintain ETL/ELT processes, data pipelines, and data structures while ensuring data quality, security, and regulatory compliance.

Qualifications

• Bachelor's degree or higher in a STEM field with strong data management foundation.
• Certifications in Oracle, SQL, Hadoop, cloud platforms, data engineering, or ETL technologies preferred.
• 5+ years of experience in Data Warehousing, Data Engineering, DB development or big data.
• Experience supporting regulatory reporting, MIS, analytics, and enterprise reporting environments.

Responsibilities

• Support implementation of the Enterprise Data Warehouse and Information Management roadmap.
• Participate in data modernization, platform enhancement, and automation initiatives.
• Evaluate opportunities to improve data architecture, processing efficiency, and system scalability.
• Contribute to technical design discussions and data solution architecture reviews.
• Support migration and integration initiatives involving cloud, big data, and enterprise platforms.
• Adhere to enterprise data management policies, development standards, and governance frameworks.
• Ensure compliance with regulatory, audit, information security, and data governance requirements.
• Maintain technical documentation, data dictionaries, mapping documents, and operational procedures.
• Participate in code reviews, release management, deployment validation, and production support activities.
• Support implementation of best practices for development, testing, monitoring, and operational support.
• Design, develop, and maintain ETL/ELT processes, data pipelines, and integration workflows.
• Build and optimize data warehouse components, data marts, and reporting data structures.
• Develop and maintain Oracle SQL, PL/SQL, and Hadoop-based solutions for enterprise data platforms.
• Ensure accurate and timely ingestion, transformation, reconciliation, and delivery of data.
• Perform root-cause analysis and resolution of data, application, and platform issues.
• Drive automation of recurring data processing and reporting activities.
• Support implementation of cloud-based and next-generation data platform capabilities.
• Ensure platform availability, reliability, performance, and scalability.
• Monitor ETL jobs, batch processes, interfaces, and platform health indicators.
• Track data quality metrics, SLA adherence, processing efficiency, and system performance.
• Investigate processing failures, data discrepancies, and performance bottlenecks.
• Provide regular updates on delivery progress, issues, and remediation actions.
• Support preparation of operational dashboards and management reports.
• Collaborate with Business, Analytics, Regulatory Reporting, Risk, Finance, Operations, and Technology teams.
• Gather and analyze functional requirements and translate them into technical solutions.
• Work closely with Data Governance teams to ensure consistent data definitions and controls.
• Coordinate with Infrastructure, Application Support, and Vendor teams for issue resolution.
• Provide technical support during user testing, implementation, and production deployments.
• Execute maker-checker-reviewer controls development and production support activities.
• Perform reconciliation, validation, and quality checks to ensure data accuracy and completeness.
• Identify and escalated risks relating to data quality, processing failures, security, and operational controls.
• Support audit reviews, control testing, and regulatory submissions.
• Ensure compliance with Information Security, Data Governance, and Regulatory Reporting policies.

Skills

Data warehousing

Data engineering

Big data technologies

Information management

Education

Bachelor's degree in computer science, engineering, IT, mathematics, statistics, data science, or related discipline

Tools

Oracle

SQL

Hadoop

Cloud platforms (Azure/AWS/GCP)

ETL technologies

Job description

Role & responsibilities :

• Support implementation of the Enterprise Data Warehouse and Information Management roadmap.
• Participate in data modernization, platform enhancement, and automation initiatives.
• Evaluate opportunities to improve data architecture, processing efficiency, and system scalability.
• Contribute to technical design discussions and data solution architecture reviews.
• Support migration and integration initiatives involving cloud, big data, and enterprise platforms.
• Adhere to enterprise data management policies, development standards, and governance frameworks.
• Ensure compliance with regulatory, audit, information security, and data governance requirements.
• Maintain technical documentation, data dictionaries, mapping documents, and operational procedures.
• Participate in code reviews, release management, deployment validation, and production support activities.
• Support implementation of best practices for development, testing, monitoring, and operational support.
• Design, develop, and maintain ETL/ELT processes, data pipelines, and integration workflows.
• Build and optimize data warehouse components, data marts, and reporting data structures.
• Develop and maintain Oracle SQL, PL/SQL, and Hadoop-based solutions for enterprise data platforms.
• Ensure accurate and timely ingestion, transformation, reconciliation, and delivery of data.
• Perform root-cause analysis and resolution of data, application, and platform issues.
• Drive automation of recurring data processing and reporting activities.
• Support implementation of cloud-based and next-generation data platform capabilities.
• Ensure platform availability, reliability, performance, and scalability.
• Monitor ETL jobs, batch processes, interfaces, and platform health indicators.
• Track data quality metrics, SLA adherence, processing efficiency, and system performance.
• Investigate processing failures, data discrepancies, and performance bottlenecks.
• Provide regular updates on delivery progress, issues, and remediation actions.
• Support preparation of operational dashboards and management reports.
• Collaborate with Business, Analytics, Regulatory Reporting, Risk, Finance, Operations, and Technology teams.
• Gather and analyze functional requirements and translate them into technical solutions.
• Work closely with Data Governance teams to ensure consistent data definitions and controls.
• Coordinate with Infrastructure, Application Support, and Vendor teams for issue resolution.
• Provide technical support during user testing, implementation, and production deployments.
• Execute maker-checker-reviewer controls development and production support activities.
• Perform reconciliation, validation, and quality checks to ensure data accuracy and completeness.
• Identify and escalated risks relating to data quality, processing failures, security, and operational controls.
• Support audit reviews, control testing, and regulatory submissions.
• Ensure compliance with Information Security, Data Governance, and Regulatory Reporting policies.
  

Preferred candidate profile

• Bachelors degree in computer science, Engineering, Information Technology, Mathematics, Statistics, Data Science, or related discipline. Postgraduate qualifications in Technology, Data Management, Analytics, or Information Systems will be an added advantage.
• Relevant certifications in Oracle, SQL, Hadoop, Cloud Platforms (Azure/AWS/GCP), Data Engineering, or ETL Technologies are preferred.
• 5+ years of experience in Data Warehousing, Data Engineering, Database Development, Big Data Technologies, or Information Management.
• Experience supporting regulatory reporting, MIS, analytics, and enterprise reporting environments.
• Exposure to cloud data platforms, data lakes, and modern data architectures is preferred.
• Strong understanding of banking data domains, customer data, transaction data, risk data, and reporting structures.