Top Data Engineer Jobs in Gurgaon

Design and scale end-to-end data architecture and real-time/batch pipelines to unify product telemetry, CRM, and billing into a single source of truth. Build data foundations for ML (feature pipelines, training datasets, low-latency scoring), define telemetry/event contracts, implement data quality, monitoring, governance, and enable self-service analytics.

The Data Engineer will design and maintain data models, develop BI solutions, integrate data, and optimize data flows while collaborating with stakeholders.

The Senior Data Analytics Engineer at MariaDB designs and builds data pipelines, writes SQL queries, develops internal tools, and translates data into actionable insights. They will collaborate closely with stakeholders and leverage AI tools to enhance analytics workflows.

The role involves creating and managing data ingestion pipelines, optimizing data workflows, and ensuring data governance and compliance in a rapidly growing fintech environment.

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 Data Solutions Engineer will develop and maintain ETL processes, manage data models, optimize T-SQL queries, and implement data processing tasks with Azure tools, ensuring efficient data flow and supporting healthcare operations.

The role involves designing, building, and maintaining data pipelines and analytics solutions using various technologies to provide insights and effective operations for business stakeholders.

The Senior Data Engineer will design and maintain scalable data pipelines, manage data warehousing on Google BigQuery, and implement CI/CD practices for data workflows.

Lead delivery of cloud-based data engineering projects using AWS and Snowflake. Design architectures, guide development and testing, mentor teams, manage stakeholders, mitigate risks, and ensure quality and on-time delivery.

The Senior Data Engineer will design and optimize ETL/ELT pipelines, manage data integration, perform data validation, and support reporting solutions using various technologies.

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.

Develop high-quality operational engineering capabilities and solutions. Collaborate with business partners, create designs, and optimize data processing pipelines using various technologies.

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.

Develop and scale data management systems for AutoML and forecasting platforms, ensuring data reliability and implementing SLAs across pipelines.

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.

Lead design, optimization, and delivery of complex data systems and pipelines; manage data engineering projects; ensure data quality; mentor junior engineers; align data solutions with business goals and provide strategic guidance.

Design, build, and maintain ETL/ELT pipelines and data integration workflows into Snowflake using Azure Data Factory and DBT. Write and optimize SQL for extraction and transformation, monitor pipeline performance, enforce data quality and governance, and collaborate with analysts, architects, and DevOps in cloud-native environments.

Lead delivery of cloud-based big data projects: design, implement, and deploy ETL/data pipelines on AWS and Snowflake. Mentor team, collaborate with stakeholders, manage risks, and ensure high-quality, timely project delivery.

Lead design, development, and optimization of complex data systems and pipelines; oversee data engineering projects; ensure data quality; align solutions with business goals; mentor junior engineers and provide strategic guidance.

Lead delivery of cloud-based data engineering projects on AWS and Snowflake. Design high-level solutions, guide development and testing, optimize performance, deploy to production, manage risks, and communicate with stakeholders while mentoring team members and ensuring agile, timely delivery.

Lead test strategy and automation for an Azure data platform modernization: validate end-to-end pipelines, ETL/ELT transformations (Medallion), data integrity in Azure SQL and Data Lake, test Snowflake/DBT integrations, develop automated SQL/Python/PySpark tests, perform performance/load testing, and track defects in Jira.

Lead Data Engineer responsible for owning end-to-end data engineering delivery: design high-level solutions, guide development and testing, deploy performant data pipelines on AWS/Snowflake, collaborate with clients and offshore teams, manage risks, and mentor engineers to ensure timely, high-quality project outcomes.

Design, build, and optimize scalable Databricks-based ETL/ELT pipelines using PySpark, Spark SQL and Delta Lake. Manage clusters, integrate cloud storage and streaming sources, ensure data quality and observability, and collaborate with data scientists and stakeholders to support analytics and ML workloads.

Senior Azure Data Engineer to design, build, and support production data pipelines using Azure Databricks, ADF, ADLS2, Python and SQL. Develop ETL from scratch, troubleshoot and debug production issues, and apply data quality, governance and MDM practices. Collaboration and strong communication required. ML engineering/Azure ML is a plus.

Lead development and optimization of complex data systems and pipelines; oversee data engineering projects; ensure data quality; mentor junior engineers; align data solutions with business goals and provide strategic guidance.