Top Data Engineer Jobs in Gurgaon

Design, build, and maintain data pipelines and processing workflows. Optimize data storage, ensure data accuracy and performance, provide technical support, and collaborate with data scientists and stakeholders to resolve data issues.

Design, build, and optimize data pipelines and storage solutions. Ensure data accuracy and performance, provide technical support, and collaborate with data scientists and stakeholders to resolve data issues.

Design and translate business needs into scalable data models, reverse-engineer physical models, analyse integration challenges, support data architecture and data movement strategy.

Design, build, and optimize data pipelines and storage solutions. Ensure data accuracy and performance, provide technical support, and collaborate with data scientists and stakeholders to resolve data issues.

Design, build, and optimize data pipelines and storage on Azure. Ensure data accuracy and performance, implement ETL orchestration with ADF and Databricks, support stakeholders, and resolve data issues while enforcing security and monitoring.

Design and implement data models; reverse-engineer physical schemas; analyze integration challenges; support data architecture and data-movement strategy; develop ETL pipelines and ensure data solutions meet business needs.

Build and maintain cloud-based ETL/ELT pipelines and Snowflake data platforms. Implement data ingestion, transformations (SQL/DBT), data quality checks, and support analytics/reporting. Collaborate with architects, engineers, and analysts, participate in Agile processes, and assist with performance tuning, monitoring, and documentation.

As a Senior Data Engineer, you will develop and maintain data pipelines for healthcare data, ensuring data quality, reliability, and adherence to enterprise standards while collaborating with architects and stakeholders.

The Senior Data Engineer will develop data ingestion, transformation, and enrichment pipelines, ensuring data quality and reliability. Responsibilities include creating Bronze and Silver data layers, using SQL and dbt for implementation, and collaborating with architects and stakeholders to align data solutions with enterprise standards.

Build, monitor, optimize, and maintain ETL/ELT pipelines using Google Cloud technologies. Develop complex SQL transformations, design dimensional data models, improve query performance and cloud cost efficiency, and ensure data integrity. Collaborate with analysts and stakeholders to translate SaaS and insurance metrics into technical solutions. Participate in code reviews, documentation, troubleshooting, and data warehouse lifecycle management while supporting US business hours.

Develop and maintain Microsoft Fabric and OneLake Lakehouse solutions across Bronze, Silver, and Gold layers. Build ingestion pipelines, CDC frameworks, data-quality controls, transformations, curated datasets, and secure views using Spark, PySpark, Python, and SQL. Support Power BI semantic models and Direct Lake consumption. Implement governance, lineage, security, monitoring, reconciliation, and operational controls while troubleshooting production issues and collaborating with architects, engineers, BI teams, and stakeholders.

Design, build, and optimize scalable GCP data pipelines and BigQuery data warehouses. Develop ETL/ELT workflows, implement data modeling, ensure data quality, optimize query performance and costs, maintain orchestration with Cloud Composer/Dataflow/Pub‑Sub, and automate deployments with CI/CD while enforcing security and governance.

Leads the design, development, and delivery of Azure-based data engineering solutions using Azure Data Factory, Azure Data Lake, Snowflake, dbt, and SQL. Integrates Guidewire and insurance data into enterprise platforms, oversees pipeline performance and reliability, establishes data quality and governance standards, supports cloud migration, and provides technical leadership to data engineering teams and stakeholders.

Develop and maintain reliable data pipelines, ELT processes, workflow orchestration, custom data connectors, and CI/CD pipelines using Airflow, Python, PySpark, Hive/Trino, SQL, and Snowflake. Collaborate with cross-functional teams, monitor and troubleshoot data workflows, validate and test data, document technical processes, and support data governance.

Design, build, and maintain scalable ETL/data pipelines and data management blueprints. Ingest, transform, and curate large complex datasets for analytics, support cloud (AWS) implementations, enable downstream consumers, and provide technical leadership and operational support to ensure data governance, quality, and automation.

Design and develop scalable data-driven solutions and pipelines using Python and SQL. Leverage Azure data services to build secure, high-performance architectures, ensuring data integrity, governance, and overall success of data projects.

Design and build scalable data pipelines and architectures on Azure using ADF, Databricks, and Synapse. Implement Kimball/Data Vault modeling, write ETL in Python and T-SQL, ensure data governance (Azure Purview), automate tests, troubleshoot issues, document processes, and collaborate across teams.

Design and develop data-driven solutions and scalable data pipelines using Python and SQL. Leverage Azure data products to build robust, secure architectures, ensuring data integrity, performance, and governance while supporting data-centric client projects.

As a hands-on data engineer, you'll build and enhance scalable data platforms, develop data pipelines, and collaborate with various teams to improve data solutions and system performance.

Design, develop, and coordinate cloud data solutions using Snowflake, Python, and AWS. Support product releases, deployments, testing, and post-install support. Collaborate with architects and tech leads, troubleshoot issues, and maintain documentation. Contribute to agile squads, adopt new technologies, and enable Fidelity Wealth business data needs.

Design, build, and maintain cloud data pipelines and architectures using SQL, Python, Snowflake, and AWS. Implement CI/CD for data workflows, use developer assistance tools, and collaborate across teams to deliver reliable data solutions.

Design, build and maintain ETL mappings and data models; write SQL and Snowflake queries; manage ETL/infrastructure on AWS (EC2); use Informatica, Control-M and ServiceNow; script in Python/Shell/PowerShell; collaborate with onshore/offshore teams and define BI delivery strategy.

Develop and maintain data pipelines and applications using Python and Pandas, apply OOP and data structures, write and optimize SQL, and communicate with stakeholders. Familiarity with Agile, DevOps/CI-CD tools (Jenkins, Git, Jira), AWS, web frameworks (Django/Flask), and Snowflake is a plus.

Lead database design, data modeling, migrations, and schema evolution across MySQL/Postgres and GCP databases. Design and operate config-driven ETL/ELT pipelines and streaming ingestion, enable CI/CD, troubleshoot data flows, and mentor offshore DB/ETL engineers.

Perform data migration/refresh from production, support Python-based data refresh framework, run post-migration fixes, validate and reconcile data, monitor and resolve batch jobs and pipeline issues, perform performance checks, and coordinate with dependent teams.