Software Engineer II A - GBS IND

Global Business Services

Process Overview*

Responsibilities*

• Key responsibilities include:
• Design, develop, and maintain data pipelines, integrations, and data processing solutions within enterprise data platforms.
• Contribute to end‑to‑end delivery of data engineering initiatives, including requirements understanding, development, testing, deployment, and production support.
• Assist in the implementation and adoption of Data Virtualization, Data Quality frameworks, Metadata Management, and Data Lineage capabilities.
• Develop scalable and reusable data integration patterns to support batch and near real‑time data processing use cases.
• Support modernization of legacy data processes by reducing manual interventions and improving automation and monitoring.
• Follow and help enforce enterprise data standards, best practices, and governance guidelines to ensure data quality, security, and compliance.
• Collaborate with architects, platform teams, governance, security, and business stakeholders to deliver aligned data solutions.
• Troubleshoot and support performance, reliability, and scalability issues in production data platforms.
• Participate in technical discussions, design reviews, and continuous improvement initiatives across the data engineering team.

Education*

Experience Range*

Foundational skills*

• Solid understanding of data engineering fundamentals, including data ingestion, transformation, integration, orchestration, and data lifecycle management.
• Strong proficiency in SQL and good programming skills in Python for building and maintaining data pipelines.
• Hands‑on experience with data integration and ETL/ELT tools such as Informatica, supporting batch and near real‑time processing.
• Working knowledge of data virtualization concepts, with exposure to platforms such as Starburst (Trino/Presto) preferred.
• Experience with relational databases such as Oracle, and familiarity with data warehouses and data lake architectures.
• Understanding of data modeling concepts, including conceptual, logical, and physical models (dimensional and normalized).
• Exposure to distributed data systems, APIs, and messaging or event‑driven integration patterns.
• Basic to intermediate understanding of Data Quality, Metadata, and Data Lineage principles.
• Familiarity with at least one cloud platform (Azure, AWS, or GCP) and cloud‑based data engineering practices.
• Working knowledge of DevOps practices, CI/CD pipelines, version control systems, and automation for data solutions.
• Awareness of data governance, security, privacy, and compliance requirements in enterprise environments.
• Strong collaboration and communication skills, with the ability to work effectively in cross‑functional teams.

Desired skills*

• Exposure to cloud‑native data services (e.g. ADLS, S3).
• Familiarity with CDC patterns, and hybrid (on‑prem + cloud) data integrations.
• Knowledge of streaming platforms such as Kafka for near real‑time data ingestion and processing.
• Experience with data observability, monitoring, and alerting tools for data pipelines.
• Understanding of master data management (MDM) and reference data concepts.
• Work Timings*: 11:30 AM to 8:30 PM IST

Job Location*

• Gurugram / GIFT City