Top Data Engineer Jobs in Gurgaon

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 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.

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

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.

Responsible for designing and developing a GCP data ecosystem, creating data pipelines, optimizing data architectures, troubleshooting issues, and mentoring junior engineers.

The Senior Data Engineer will design, build, and maintain data platforms and pipelines, ensuring data security and efficiency while collaborating with stakeholders.

Design and maintain scalable data pipelines using Google Cloud services, ensure data quality, and collaborate with stakeholders to deliver data solutions.

As a Data Engineer, you will design, develop, and maintain data integration solutions, optimize ETL/ELT pipelines, and support data workflows for analytics and reporting.

The role involves designing scalable data pipelines and architectures using Microsoft Fabric, client engagement for requirements gathering, and optimizing data solutions for analytics and reporting.

Design, build, and optimize ETL/ELT data pipelines and curated lake/warehouse models for procurement. Partner with stakeholders to translate requirements, deliver dashboards, maintain data quality, APIs and automation, and collaborate on design, reviews, and platform improvements.

Design, build, and optimize data pipelines, ETL/ELT processes, and scalable lake/warehouse data models for procurement reporting. Partner with stakeholders to translate requirements, implement data quality and governance, develop extracts/APIs and dashboards, and improve performance and reliability through collaboration and code reviews.

Senior technical leader responsible for designing, building, and scaling cloud-native data platforms and pipelines. Partners with stakeholders, mentors engineers, enforces engineering best practices, ensures data modeling, governance, and quality, debugs production issues, and contributes to architecture, design, and Agile delivery to support business outcomes.

Build and operate automated data quality checks, monitoring, alerting, and dashboards; integrate quality into data pipelines and governance tooling; automate anomaly detection and support auditors, analysts, and stewards to surface issues in near-real-time.

The Senior Data Engineer will build and optimize data pipelines in Azure Databricks, migrate existing pipelines from Azure Synapse, and design scalable data models to support a financial services client's data platform modernization.

As a Senior Engineer for Strategic Data Solutions, you will manage data warehousing, reporting, and analytics for internal operations and external partners. Responsibilities include collaborating with business units, providing insights, and ensuring high-quality data reporting.

Own and maintain analytics instrumentation and data pipelines using Segment, ensuring reliable event tracking to Mixpanel, GA4 and AppsFlyer. Use Terraform for version-controlled analytics infrastructure, monitor and audit data quality, maintain schema documentation, translate business needs into tracking, and configure mobile/web attribution and deep-linking.

The Snowflake Senior Data Engineer will lead projects in data engineering, utilizing Snowflake and various AWS services to optimize data workflows and storage, while also guiding the team and collaborating with stakeholders.

Design, build, and optimize scalable data pipelines and models using Spark, Kafka, Airflow, dbt, and SQL across GCP and AWS. Ingest and normalize marketing and analytics data, ensure data quality and governance, support analytics and reporting, and collaborate with cross-functional global teams.

Design, operate, and secure scalable batch and streaming data pipelines and platforms. Own ingestion, transformation, serving, data quality, and access controls. Partner with product, risk, compliance, and InfoSec to ensure production reliability, correctness, and audit readiness for financial data.

The Data and Application Integration Engineer will design and implement application integrations, migrate legacy processes, manage data quality, and support CI/CD pipelines.

As a Data Engineer, you will design and maintain data pipelines, enhance blockchain reporting, and ensure data quality while integrating external data sources and working with various teams.

Lead the design and implementation of data engineering solutions on AWS, focusing on scalable data pipelines, data lakes, and warehouses, while mentoring teams and ensuring data quality.

As a Data Engineer, you will design and develop data pipelines, ensuring data quality and scalability. You'll collaborate with teams to meet business needs and mentor junior members.

Build and maintain high-performance ETL/ELT pipelines and analytics-ready data warehouses using Python, Pandas (and Polars). Optimize for speed, memory, and parallelism; write complex SQL/PLSQL queries including window functions; perform validation, monitoring, debugging and production support; document workflows and collaborate with cross-functional teams.