Senior Data Engineer

Role Overview

We are looking for an experienced Senior Data Engineer with strong expertise in SQL/PLSQL, data engineering, ETL/ELT, data transformation, and Snowflake. The candidate will design, develop, and maintain scalable data pipelines and transformation processes across enterprise data platforms. The role requires strong hands-on technical capabilities along with a sound understanding of data integration, data quality, performance optimization, and cloud-based data engineering. Experience or training in Denodo would be an added advantage.

Key Responsibilities

• Design, develop, and maintain robust ETL/ELT data pipelines for batch and data integration workloads.
• Develop complex SQL and PL/SQL queries, procedures, functions, and transformation logic.
• Build and maintain data ingestion and transformation processes in Snowflake.
• Perform data extraction, cleansing, transformation, integration, and loading across multiple source systems.
• Develop reusable and scalable transformation frameworks for enterprise data workloads.
• Work with structured and semi-structured datasets from different source systems.
• Perform SQL query optimization, performance tuning, and troubleshooting.
• Design and implement data validation and data quality checks within pipelines.
• Troubleshoot data pipeline failures, data inconsistencies, and performance issues.
• Work with cloud platforms such as AWS, GCP, or Microsoft Azure for data engineering workloads.
• Collaborate with data architects, analysts, application teams, and business stakeholders to translate data requirements into technical solutions.
• Support documentation, deployment, monitoring, and continuous improvement of data engineering solutions.
• Contribute Denodo and data virtualization knowledge where applicable.

Mandatory Technical Skills

• Strong hands-on expertise in SQL and PL/SQL.
• Data engineering and enterprise data pipeline development.
• ETL and ELT job development, orchestration, and transformation.
• Snowflake data ingestion, transformation, and performance optimization.
• Complex SQL queries, stored procedures, functions, and query tuning.
• Data validation, reconciliation, and data quality controls.
• Cloud data engineering experience on at least one platform: AWS, GCP, or Microsoft Azure.
• Experience handling large enterprise datasets and integrating multiple data sources.

Good to Have

• Denodo training, certification, or hands-on working experience.
• Understanding of data virtualization concepts and architecture.
• Experience integrating databases, enterprise applications, APIs, and cloud data sources.
• Experience with enterprise data warehouse and data lake architectures.
• Understanding of CI/CD and version-control practices for data engineering.
• Exposure to Python or another scripting language for data engineering activities.
• Knowledge of data governance, metadata management, and access-control concepts.

L1/L2 Interview: VirtualWork Mode: HybridWork Location: Gurgaon