Top Data Engineer Jobs in Gurgaon

Lead technology solution delivery for clients by managing projects, translating requirements, mentoring teams, and ensuring high-quality outcomes through collaboration and innovation.

Design, build, and operate large-scale enterprise data platforms leveraging AI/ML to optimize data pipelines and support analytics and GenAI workloads.

The role involves building HR data solutions, utilizing Workday for reporting, and migrating data to Snowflake, while ensuring data privacy and quality.

The role involves designing and building data systems using various technologies, especially within Microsoft Azure, and requires experience in system integration and data warehousing.

We are seeking Data Engineers to migrate dashboards from Hadoop to GCP, ensuring data consistency, accuracy, and collaborating with cross-functional teams.

Design and maintain scalable data pipelines, optimize data models, and collaborate with teams to support analytics and reporting needs.

As a Data Engineer, you will design and maintain scalable data pipelines, manage databases, and implement ETL processes, collaborating across teams.

The Data Engineer will design and build scalable data pipelines on GCP, perform data ingestion and transformation, and collaborate with stakeholders to deliver data solutions.

Design, build, and optimize scalable data pipelines on Azure using Databricks and Spark. Implement CI/CD, performance tuning, debugging, and collaborate with stakeholders to deliver production-grade data solutions.

As a Data Engineer, you will design, build, and maintain scalable data platforms and pipelines, optimizing workflows and ensuring security.

As a Senior Data Engineer, you will architect system migration to Oracle Cloud, integrate AI/ML solutions, and lead data quality initiatives.

The Data Engineer is responsible for developing ETL/ELT pipelines, managing data warehousing, processing data with Python, and collaborating with stakeholders to meet data needs.

Design, implement, and manage data infrastructure, build ETL/ELT pipelines, and collaborate with stakeholders to support analytics and BI initiatives.

Lead the maintenance and expansion of reporting platforms, develop data transformations in SQL, manage junior engineers, and ensure data quality on Google Cloud Platform.

As a Senior Analyst-Data Engineer, you will design, develop, and optimize data pipelines, ensure data quality and transform marketing data into insights.

The Data Engineer will manage product lifecycle projects by ensuring data accuracy across systems and improve data processes throughout the company.

The Data Engineer will manage and maintain data integrity across systems, support product lifecycle projects, ensure compliance with standards, and drive improvements in data processes.

The Senior Azure Data Engineer will design, develop, and maintain data infrastructure and pipelines, ensuring data quality, integrity, and alignment with business objectives. Responsibilities include collaborating with teams and establishing best practices for data engineering.

As a Data Engineer III, you will design and develop scalable cloud-native solutions, build data pipelines for LLM-based AI systems, and mentor junior developers.

As a Data Engineer, you will enhance data pipelines, support ML workflows, and improve cloud infrastructure on Azure and AWS, collaborating with Scientists and Engineers to turn data into actionable insights.

We are looking for a Data Engineer with skills in Python, SQL, and Azure technologies to develop Big Data applications. Responsibilities include working with Spark and Docker to handle large scale data processing and analytics.

The Azure Data Engineer will implement big data pipelines using Azure technologies, collaborate with stakeholders, and utilize tools like Data Factory and Databricks.

The Azure Data Engineer will build data pipelines and dataflows, implement security modules, and work with Azure services while supporting business requirements and data analysis.

The Data Engineer role involves analyzing raw data, building data systems, conducting complex analyses, and enhancing data quality by collaborating with data scientists and architects.

This role involves collaborating with users to build data solutions, managing AWS data technologies, and automating workflows for efficiency.