Top Data Engineer Jobs in Pune

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.

Lead design and implementation of scalable data platforms using Microsoft Fabric. Build and optimize pipelines, lakehouses/warehouses, and semantic models/ontologies. Ensure data quality, governance, metadata management, and semantic consistency. Collaborate with stakeholders to enable analytics, AI/ML initiatives, and business insights using Python and modern data frameworks.

As a Lead Data Engineer, you'll build and maintain data systems, ensure data accuracy, collaborate with data scientists, and advise on policy and operational effectiveness, all while leading a team in complex data architecture projects.

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.

Design, implement, and support analytical data infrastructure and real-time pipelines. Build ETL processes and data warehousing using SQL and AWS big-data services. Collaborate on analytics, monitoring, and machine-learning implementations, and improve automated reporting and self-service capabilities.

Provide Level 3 escalation and expert technical support for enterprise IT infrastructure across multi-client data centre environments. Design, implement, troubleshoot, and optimize Windows Server, virtualization (VMware/Hyper-V/NSX), storage, backups, Active Directory, and hybrid Azure/Microsoft 365 systems. Standardize configurations, document SOPs, automate provisioning and patching, collaborate with network/security teams, mentor junior engineers, and lead Tiger Team projects.

This role involves leading SAP data migration projects, developing ETL processes, ensuring data quality, and collaborating with cross-functional teams to optimize data integration and management strategies in SAP environments.

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 Data Engineer to design, build, and operate production data pipelines, retrieval/vector infrastructure, semantic/feature stores, and ML/LLMOps foundations. Drive CI/CD, governance, monitoring, and agent/data APIs for RAG, LLM, and predictive model workloads.

Design, build, monitor and scale an enterprise data warehouse and pipelines. Lead data integration, ETL design, source-to-target mapping, reusable frameworks, automated testing/CI, and partner with stakeholders to deliver secure, governed analytics for product, marketing and HR use cases.

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.

Design and develop large-scale database systems, optimize performance, and implement automation for managed database services. Collaborate across teams to enhance data access and ensure governance for security and compliance.

The role involves building data lakes, developing data pipelines, ensuring data quality, collaborating with teams for analytics, and maintaining data dashboards.

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 maintain enterprise-scale data pipelines, data lakes/warehouses and lakehouse architectures on AWS. Implement Spark-based (Scala/PySpark) processing, ensure data quality/validation, deploy production-ready pipelines with IaC (Terraform), use orchestration (Airflow), collaborate with data scientists for ML deployment, and operate governed solutions using Apache Iceberg, dbt, Snowflake/Databricks integrations.

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, build, and maintain production data pipelines and models using Python and SQL. Improve data architectures (Kafka, warehouses, ODS), optimize SQL performance, perform data cleaning and analysis, select data sources, and collaborate with partners to support cloud-based analytics (Snowflake, AWS SageMaker) and workflow tools like Airflow.

Design, build, and maintain scalable Microsoft Fabric and Azure-based data platforms, ETL/ELT pipelines, lakehouse and data warehouse architectures. Implement orchestration, monitoring, data quality, CI/CD, and support analytics, AI, and production operations while following Specification-Driven Development practices.

Lead design and support of analytical data infrastructure and real-time data pipelines on AWS. Build ETL, data modeling, warehousing, and BI solutions; collaborate on analytics and machine learning integrations; automate reporting and improve self-service access.

Lead site-based CSA activities for data centre projects: manage contractors, ensure compliance with design, safety and quality, coordinate stakeholders, produce reports, and support project leadership.

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.

Lead multiple data engineering teams to design, build, and govern scalable ELT pipelines and cloud-native data products. Ensure adherence to enterprise data models, CI/CD, data governance, metadata/lineage, monitoring, and performance optimization (Snowflake). Mentor engineers and collaborate with architects, analysts, and BI to deliver reusable, efficient data solutions.

Lead design and implementation of cloud-native ETL/ELT pipelines and data warehouse solutions. Optimize performance, ensure data quality and governance, mentor engineers, automate workflows, and collaborate with cross-functional teams to support analytics and BI initiatives.