Top Data Engineer Jobs in Delhi

Support electrical design, engineering, commissioning, and delivery of liquid-cooled data centre solutions: prepare layouts, SLDs, wiring diagrams, BOMs, perform load calculations, assist testing/FAT/SAT, troubleshoot commissioning issues, coordinate cross-functional teams, and ensure compliance with IEC/NEC/IEEE and company HSE standards.

Design, build, test, and maintain backend applications, APIs, and ETL/ELT data pipelines. Perform data transformation, validation, statistical analysis, and optimize code, queries, and pipelines. Troubleshoot production issues, collaborate with cross-functional teams, participate in code reviews, and document architectures and data workflows.

Design, build, and maintain scalable ETL pipelines and Python data workflows. Perform statistical analysis, optimize queries and pipelines, clean and validate large datasets, troubleshoot failures, document solutions, and collaborate with cross-functional teams to deliver reliable data solutions and insights.

Design, implement, and lead large-scale generative AI and ML systems (LLM fine-tuning, RAG, agents, Graph ML). Build REST APIs, deploy with Docker/Kubernetes, optimize big-data workflows, mentor engineers, and operate ML services on cloud platforms.

Own and automate end-to-end incentive calculation pipelines, translate business rules into auditable data workflows, build monitoring and reconciliation dashboards, ensure accuracy and auditability across multiple products and countries, and partner with Sales, Finance, and field teams to resolve discrepancies and support escalations.

Build and maintain end-to-end data pipelines using PySpark and SQL on Databricks/Delta. Establish data modeling and pipeline best practices, create AI-ready analytical datasets, troubleshoot pipeline issues, and collaborate with stakeholders to embed business logic and optimize reliability, efficiency, and performance.

Design, build, and operate batch and real-time data ingestion and transformation pipelines. Develop platform components (storage, compute, pipelines), monitoring, alerting, and data-quality tooling. Diagnose production issues, participate in on-call rotations, and build AI-powered agents to automate engineering and operational tasks.

As a Data Engineer, you'll build and monitor large-scale data pipelines, develop the DBT setup for data transformation and solve customer problems using your SQL skills.

The IT Operations Engineer will manage AI and Data platforms, ensure operational health, lead incident resolution, and automate tasks while collaborating with engineering teams.

Manage and support AKS-based enterprise data platform infrastructure, administer Apache NiFi, Azure Event Hub and Functions, implement CI/CD with Azure DevOps, automate infrastructure with Terraform/Bicep/ARM, monitor with Azure Monitor and Log Analytics, troubleshoot production incidents, ensure security, capacity planning, and collaborate with data engineering teams.

As a Lead Data Engineer, you will design and manage data pipelines, develop ETL processes, and ensure data quality. Mentorship of junior engineers is also part of the role.

Lead the architecture and implementation of a distributed data platform for microscopy, ensuring scalability and high-performance in data management.

As a Lead Engineer, you'll design and develop frameworks and services for HighLevel's platform, optimizing large-scale database clusters and ensuring performance and security across multiple environments.

As a Senior Data Engineer, you will architect the AI-native Data Platform, optimize performance, ensure data governance, and mentor engineers on best practices.

Design, build, and optimize high-volume data pipelines using Python, Databricks and Spark on Azure. Create and maintain automation test suites (Azure DevOps), perform manual/load/exploratory testing, collaborate with BAs and developers to meet sprint goals, and assist with sprint estimation and delivery.

Design, develop, and deploy data engineering solutions and analytics pipelines on Databricks. Build data models, optimize SQL and DAX queries, manage ETL and real-time ingestion, tune performance for large data volumes, and produce dashboards and reports while cross-training team members.

The Senior Data Scientist & Engineer will build and manage data infrastructure, analyze product usage, build models, track metrics, run experiments, and communicate insights to guide product decisions.