Overview

Title: Data Engineer-Husky (Guindy,Chennai)

Responsibilities

• The Data Engineer within the Husky DST Data Team will play a key role in supporting and advancing Husky’s enterprise‑wide Business Intelligence and Data Management ecosystem. Working as part of the global DST organization, this role is responsible for ensuring the reliability, performance, and scalability of the Enterprise Data Warehouse (EDW) and associated data pipelines across both on‑premises and Azure cloud environments.
• The Data Engineer will proactively monitor and optimize back‑end data load processes, contribute to the design, development, and deployment of data integration and transformation solutions, and ensure adherence to data governance and development lifecycle standards. In addition, this role will support Data Management initiatives aimed at meeting Husky’s evolving information needs, including data quality, metadata, and master data management activities.
• The position will also lead infrastructure capacity assessments, performance tuning efforts, and recommendations for architectural improvements to ensure the long‑term efficiency and sustainability of Husky’s data platforms.
• Execute end‑to‑end Enterprise Business Intelligence and Data Engineering initiatives, including requirement analysis, BI specification development, data modeling, solution design, deployment, and post‑production support.
• Serve as a technical consultant and facilitator between cross‑functional teams, ensuring effective communication and alignment among business units, project teams, and technical stakeholders.
• Perform root‑cause analysis and drive timely resolution of production issues, ensuring minimal disruption to BI processes and data platforms.
• Support both pre‑production and production data infrastructure environments, ensuring stability, performance, and adherence to operational standards.
• Participate in planning, preparation, and execution of periodic software releases, ensuring smooth deployment of enhancements, patches, and new features.
• Collaborate closely with project teams, business stakeholders, and leadership, translating business needs into scalable and maintainable data solutions.
• Coordinate with internal and external partners, such as vendors, integration teams, and cloud service providers, to ensure seamless project delivery and system operations.
• Conduct detailed requirements analysis and documentation, ensuring clarity, completeness, and alignment with enterprise architecture guidelines.
• Execute assigned project tasks and deliverables, contributing to successful completion of work packages within scope, timeline, and quality expectations.
• Perform advanced data analysis, data profiling, and validation to support data modeling, quality assessments, and integration design.
• Support the program manager in planning, coordination, and delivery of the overall Enterprise Business Intelligence program, ensuring alignment with strategic objectives.
• Ensure adherence to enterprise quality standards, including coding best practices, documentation, testing, and data governance policies.
• Contribute to Master Data Management (MDM) initiatives, supporting data quality, standardization, and stewardship processes across the organization.

Education

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related technical discipline.
• 5–10 years of experience working in data engineering, business intelligence, or analytics‑focused roles within complex enterprise environments.
• Proven experience delivering and supporting Business Intelligence, Data Warehouse, and Data Integration solutions at scale.
• Experience working in global or multinational environments is an asset.
• Understanding of manufacturing and sales business processes is considered beneficial.
• Strong hands‑on experience with ETL/ELT development involving medium to high complexity integration pipelines, ensuring high availability, data quality, and reliability in production environments.
• Proficient with a broad range of Microsoft data and analytics technologies, including:
• Databases & Platforms: SQL Server 2019/2022
• Data Integration: SSIS, Azure Data Factory (ADF)
• Analytics & Modeling: SSAS, Power BI
• Cloud: Azure Synapse, Azure Data Lake, and related Azure data engineering services
• Programming & Scripting: T‑SQL, PowerShell, VBA, VBScript
• Familiarity with Data Warehouse Automation tools such as dbt (Data Build Tool) is a strong advantage.
• Familiarity with Data Replication tools such as FiveTran is an advantage.
• Strong understanding of server operational environments, particularly Windows Server 2019/2022.
• Experience implementing and supporting DevOps practices, including CI/CD pipelines, automated deployments, and version control.
• Demonstrated expertise in data analysis, data profiling, and root‑cause investigation across complex datasets and pipelines.
• Strong analytical and troubleshooting abilities with the capacity to diagnose application, data quality, and system performance issues.
• Ability to monitor, evaluate, and interpret ETL results, collaborating closely with operations and delivery teams to drive improvements in data quality and platform stability.
• Excellent written and verbal communication and presentation skills, with the ability to translate technical concepts for non‑technical audiences.
• Strong facilitation skills, capable of moderating meetings, workshops, and design sessions to support effective decision‑making.
• Ability to work collaboratively with cross‑functional teams, internal partners, and external vendors.
• Fluency in English is required.
• German and French language skills are considered an asset.