Top Data Engineer Jobs in Delhi

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.

Build and maintain scalable ETL pipelines on GCP, transform large/disconnected datasets, automate and optimize data delivery, support stakeholders, and apply data engineering best practices including testing and release management.

Design, build, and maintain scalable ETL/ELT pipelines and microservices for marketing and product data, ingesting from ad platforms (especially Meta Ads) and event systems. Enable campaign performance tracking, lead funnel analysis, attribution, and revenue reporting. Ensure data quality, observability, governance, and documentation while collaborating with marketing, growth, and analytics to deliver actionable datasets and drive business outcomes.

Design, build, and maintain scalable ETL/ELT data pipelines on GCP/BigQuery using Python and Spark. Integrate systems (APIs, Oracle EBS), implement workflow orchestration, ensure data quality and security, monitor performance, and document processes while collaborating with analysts and business teams.

Design, build, and optimize Snowflake data models and dbt pipelines. Create Power BI reports and paginated RDLs with DAX and row-level security. Manage CI/CD with Azure DevOps, version control with Git, enforce data quality and governance, and optimize warehouse cost and performance while collaborating with business stakeholders.

Build and prepare data pipelines: mapping, cleansing, transformation, integration, and wrangling using Python and SQL. Perform feature engineering for structured and unstructured data and support API and web app deployment for data products.

The Python Data Engineer is responsible for developing Python applications, designing ETL pipelines, integrating APIs, and managing data solutions to enable data-driven decision making.

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

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.

The Data Engineer will build and maintain ETL/ELT pipelines in Microsoft Fabric, transforming data for analytics and reporting while collaborating with global teams.

The role involves onboarding cybersecurity data sources, mapping and normalizing data, customizing workflows, and collaborating with teams to enhance security measures.

As a Data Engineer, you will build and maintain data systems for drug safety AI tools, ensuring reliable data processing and storage for research teams.

The Sr. Staff Integration Engineer will onboard cybersecurity data sources, normalize security data, troubleshoot pipeline health, and communicate with stakeholders to enhance product integration and performance.

The Data Engineer designs and develops data pipelines for storage and processing, optimizes data integration, and collaborates with analysts on data models and KPIs, while leveraging cloud and AI technologies.

The Big Data Engineer will design and develop scalable data solutions, build data pipelines, ensure data quality, and collaborate across teams.

The role involves managing data pipelines in cybersecurity, collaborating with teams to implement solutions, and troubleshooting issues efficiently using Python and SQL.

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.

As a Product Engineer, you will ensure quality and usability of geospatial AI tools, design test plans, validate software, and document technical processes.

Own end-to-end design and delivery of IoT and real-time data platform features: define architecture, build Node.js backends and React/Vue dashboards, integrate device telemetry (MQTT/WebSockets), manage MongoDB and time-series data, ensure CI/CD and cloud deployments, and mentor junior developers.

Data Engineer responsibilities include designing and building scalable data management systems, optimizing data pipelines, managing data warehouses, and ensuring data quality and compliance.

The Data Engineer role involves designing and maintaining data pipelines, ensuring data quality, integrating data sources, and collaborating across teams to enhance BitGo's data infrastructure.

Build and maintain AWS serverless applications and data pipelines using Python and Node.js, implement authentication via Cognito and Lambda triggers, develop REST/GraphQL APIs and React frontends, author IaC with Terraform/CloudFormation, integrate CI/CD, ensure security/compliance, and support integrations such as webhooks and event streams.