Top Data Engineer Jobs in Delhi

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.

Data Engineer responsible for building and maintaining ETL pipelines, data processing workflows, and data platforms. Must have strong hands-on experience with Healthcare Revenue Cycle Management and understanding of healthcare data workflows. Role requires hybrid (onsite + offshore) work and immediate availability.

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.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Design, implement, and maintain data pipelines using Elasticsearch and data warehousing solutions, integrate data sources, and ensure data accuracy while collaborating with cross-functional teams.

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.

Design, build, and maintain dbt models and Snowflake data warehouses, own CI/CD and orchestration for pipelines, implement data quality tests, partner with stakeholders to translate requirements into production-ready data models, and optimize performance and observability.

Join Speechify to lead data collection efforts for AI model training, optimizing cloud infrastructure and collaborating on dataset roadmaps for improving text-to-speech products.

As a Data Engineer, you will build scalable ETL/ELT pipelines, optimize data structures, and develop impactful Power BI solutions for stakeholders.

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

Build and oversee scalable data infrastructure, ETL and orchestration pipelines, APIs, open-data platforms, and dataset migrations. Document data workflows, ensure licensing, metadata, and PII compliance, and collaborate with public-sector stakeholders. Lead project planning, align engineering work with product roadmaps, mentor data engineers, conduct code reviews, and support dashboards and AI-ready data transformation.

As a Data Engineer, you will analyze and enrich structured and unstructured data, enhance data quality, and develop insights for financial strategies.

Design and build a greenfield, multi-layer data warehouse and semantic metrics layer; separate analytics from OLTP; ensure data quality, traceability, tenant isolation, and high SLAs; enable linking of structured records to drone imagery/video; deliver self-service data access, observability, and infrastructure automation to scale across products and tenants.

Leads a team of data engineers and owns the architecture, implementation, governance, security, and optimization of a GCP Data Lakehouse platform. Responsibilities include designing Spark and Delta Lake pipelines, managing Unity Catalog, improving SQL and ETL performance, enabling analytics and machine learning use cases, implementing CI/CD with GitLab and Jenkins, and communicating technical strategies to stakeholders.

The Data Platform Engineer assists with data platform blueprint and design, integrating systems and data models with Integration and Data Architects. Responsibilities include leading teams, making technical decisions, solving cross-team problems, optimizing data workflows, and sharing knowledge. The role requires strong Snowflake expertise, SnowPro Core Certification, data modeling, ETL, cloud data architecture, SQL, and at least 7.5 years of experience. The position is based in Gurugram.

Build and enhance enterprise data pipelines into Databricks Unity Catalog and Delta Lake. Improve remediation and entity-matching layers (including D&B DataBlocks), integrate APIs, and support LLM-assisted remediation and CMG redesign projects.

The Senior Data Engineer will build data pipelines, implement data governance, automate processes, and enhance data tooling to improve insights across teams.

The Data Engineer role involves designing and maintaining ETL pipelines, optimizing data storage solutions, collaborating with teams, and ensuring data accuracy and integrity.

Design, build, and maintain centralized data pipelines, warehouses, lakes and hubs. Assemble complex datasets, implement ETL processes, build analytics tools and reports, support cross-functional teams, ensure secure cross-region data separation, and create product data tools to enable insights on acquisition and operational metrics.

Build and maintain scalable batch and real-time data pipelines using Kafka, Maxwell, Spark and dbt; design medallion-based data models; implement cloud-native data platforms (S3, Trino, BigQuery); optimize performance, ensure data quality, observability, and SLA adherence; enable analytics through trusted datasets and Metabase dashboards.

Design, build, and maintain scalable cloud-native batch and streaming data platforms and pipelines. Own end-to-end solutioning, deployment, production support, performance tuning, monitoring, and mentorship while collaborating with product, analytics, and infrastructure teams.

Design, build, and maintain scalable Java Spring Boot backend microservices integrated with blockchain/Web3 infrastructure. Develop REST APIs, event-driven systems (Kafka/JMS), SQL/NoSQL data stores, and containerized cloud deployments (Kubernetes). Ensure performance, security, and reliability while collaborating with cross-functional teams in Agile environments.

Design, build, and optimize large-scale ETL pipelines and distributed data applications (batch and streaming) using Spark and Scala. Ensure data quality and performance, deploy and manage workloads in cloud/container environments, troubleshoot production issues, and collaborate with product, engineering, and analytics teams to deliver scalable AdTech data solutions.

Design, build, and operate scalable batch and real-time data pipelines and analytics platforms. Partner with enterprise customers to define requirements, own technical delivery from discovery to adoption, and present architectures to stakeholders. Drive data governance, observability, CI/CD, and platform optimization while mentoring junior engineers and collaborating with Product, Engineering, and Customer Success teams to enable analytics and AI/ML applications.

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.