Data Engineer-Husky (Guindy,Chennai)

• 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.

Qualifications: 

Education & Experience

• 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.

Technical Skills

• 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.

Analytical & Problem‑Solving Capabilities

• 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.

Soft Skills & Collaboration

• 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,