Senior Data Engineer

Location: Gurugram, India (Onsite)

Experience: 5+ years

Employment Type: Full-time

We are hiring a Senior Data Engineer with a proven track record in building scalable data pipelines and data platforms. The ideal candidate will have more than 5 years of experience in data engineering, with working knowledge of data governance tools and data labelling practices to support analytics and AI/ML initiatives.

This is a full-time onsite role based in Gurugram, and candidates should be open to collaborating closely with cross-functional teams.

• Design, develop, and manage scalable and secure data pipelines for batch and real-time processing.
• Build and maintain data lake/data warehouse architectures across cloud environments.
• Collaborate with data scientists, analysts, and business teams to deliver clean, reliable, and accessible datasets.
• Implement data governance frameworks including metadata management, data cataloging, lineage tracking, and access controls.
• Support data labelling efforts for AI/ML pipelines by integrating tools or enabling manual/automated labelling workflows.
• Monitor and optimize data workflows for performance, cost-efficiency, and reliability.
• Maintain high data quality standards through validation, testing, and documentation.
• Contribute to architectural discussions and mentor junior engineers.

• Minimum 5 years of experience in data engineering or related fields.
• Strong experience with data pipeline development using tools like Apache Spark, Kafka, Airflow, or similar.
• Proficient in Python and SQL for data transformation and automation.
• Experience working on cloud platforms such as AWS, GCP, or Azure (at least one, familiarity with others is a plus).
• Hands-on experience with data warehousing solutions like Snowflake, BigQuery, Redshift, or Synapse.
• Familiarity with data governance tools (e.g., Collibra, Alation, Apache Atlas, or cloud-native governance tools).
• Understanding of data labelling workflows and experience supporting ML-ready datasets.
• Strong understanding of data modeling, data quality, and data security best practices.
• Excellent communication and collaboration skills.

• Experience with infrastructure as code (Terraform, CloudFormation).
• Exposure to ML pipelines, feature stores, or automated data labeling tools.
• Knowledge of data observability and monitoring frameworks.

• Opportunity to work on high-impact data projects across diverse industries.
• Collaborative and innovation-driven work environment.
• Be part of a growing team building modern data platforms from the ground up.