π Hiring: Data Engineering Lead
π Location: Delhi / Noida (Only local candidates)
πΌ Experience: 8+ Years
π― Role Overview
We are looking for an experienced Data Engineering Lead to design, build, and manage scalable data platforms supporting analytics and AI/ML initiatives. The ideal candidate will have strong expertise in data architecture, pipeline development, and governance, along with experience working on large-scale datasets.
π Educational Qualification
B. Tech / M. Tech / MS in Computer Science, Data Engineering, or related fields
Certifications in cloud platforms (AWS / Azure / GCP) are a plus
π§ Experience
8β12 years in data engineering or data platform architecture
4β5 years of experience building large-scale data pipelines for analytics/AI
5β7 years in designing enterprise data architectures
Hands-on experience with structured, semi-structured, and unstructured data
π§ Key Responsibilities
Architect and implement scalable data pipelines for AI/ML and analytics
Design and manage data warehouse solutions aligned with government standards (NeGD / MeitY)
Build real-time and batch data ingestion frameworks
Establish metadata management, data lineage, and governance frameworks
Optimize data storage, retrieval, and compression strategies
Collaborate with AI/ML teams for high-quality, versioned datasets
Integrate APIs and connectors across Digital India platforms
Ensure compliance with data privacy, security, and retention policies
π» Technical Skills
Cloud Platforms:
AWS (Redshift, Glue, S3)
Azure Synapse
GCP (BigQuery, Dataflow)
Big Data Technologies:
Apache Spark, Hadoop, Kafka, Airflow
Databricks, Snowflake
Programming:
Python, Scala, Java, SQL
Databases:
PostgreSQL, MongoDB, Cassandra, Elasticsearch
Data Engineering Practices:
ETL/ELT design, schema evolution
DataOps, CI/CD pipelines
Infrastructure & Tools:
Docker, Kubernetes, Terraform, Jenkins
Data Governance:
Data cataloging, access control, encryption, compliance logging
π© How to Apply
Interested candidates can share their CV at:
π§
[email protected]