Top Data Engineer Jobs in Delhi

Design, build, and maintain cloud-native data pipelines and ETL/ELT workflows for high-volume trade lifecycle data. Integrate DTCC sources (RTTM, Settlement Web) into a Unified Trade Record, process ISO 15022 messages, manage trade exception databases, optimize SQL Server performance, and ensure data quality, lineage, governance, and observability while collaborating with business stakeholders.

Deploy, configure, and operate Rhombus Power's AI platform across cloud, on-premises, and edge environments. Install and validate hardware, networking, and compute infrastructure; support AWS, Docker, containerized applications, CI/CD, monitoring, and troubleshooting. Perform site readiness, rack mounting, backups, UAT, and disaster recovery. Act as on-site technical liaison, maintain deployment documentation, escalate issues, and provide ongoing operational support for defense customers.

Design, build, and maintain scalable ETL pipelines and medallion-schema data architectures. Ensure data quality, perform cleaning and migration, integrate varied sources, and support reporting and analytics in collaboration with stakeholders.

Design, build, and maintain scalable ETL/ELT pipelines and data warehouses using Snowflake, AWS Glue, Python, and SQL. Optimize performance, implement CI/CD with Azure DevOps, ensure data quality and governance, collaborate with analytics teams, and troubleshoot pipeline issues.

Principal Data Engineer responsible for building big-data solutions using PySpark and Databricks, writing and optimizing SQL, developing Python pipelines, and working with Hadoop/Hive, Git, Airflow/Dagster, and Azure.

The Senior Associate Data Engineer develops structured datasets for analysis, manages ETL processes, and designs data models to support business analytics and reporting.

Develop and enhance Snowflake-native and Java backend applications. Participate across the SDLC, collaborate with architects and developers, follow Agile and TDD practices, implement CI/CD and version control strategies, and deliver features addressing performance, security, and reusability.

Develop and enhance Snowflake-native apps and Java backend services. Participate in full SDLC, follow Agile and TDD practices, implement CI/CD, collaborate with architects and developers to design solutions, and deliver features with attention to performance, security, and code reusability.

Design, build, and maintain scalable Snowflake data pipelines and ELT/ETL workflows. Optimize Snowflake performance, manage ingestion from databases, APIs and files, implement data models (star schema), support BI consumers, and maintain pipeline health and documentation.

Design, build, and optimize ETL pipelines and data warehouses using SQL, AWS Glue, and S3. Investigate and resolve data issues, develop Python-based solutions and small web apps, and own requirements, design, and end-to-end delivery for change requests.

Design, build, and maintain scalable Snowflake-based data warehouses and ETL/ELT pipelines. Develop complex SQL and Snowflake stored procedures, implement CDC and incremental loads, optimize performance and cost, monitor pipelines, and perform data validation and reconciliation.

Provide onsite acquisition and analysis of drilling data during rig operations, install and maintain GEOLOG systems, perform real-time monitoring, generate technical logs and reports, act as first-line client technical support, and manage/train mud logging team while ensuring rig safety compliance.

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

Build and operate a scalable data platform: design and maintain ETL/ELT pipelines, Bronze/Silver/Gold data layers, data models and semantic layers, manage migrations and schema changes, ensure data quality/observability, enable analytics and future event-driven/recommendation systems, and use AI-assisted workflows to accelerate engineering.

Design, build, and maintain scalable Azure-based data pipelines and systems (Databricks, Data Lake, Synapse, ADF). Collaborate with cross-functional teams, ensure data quality and integrity, optimize performance, monitor and troubleshoot systems, and stay current with industry trends to improve solutions.

Design, document, and implement data pipelines and transformations (dbt, Airflow) feeding Snowflake warehouses. Ensure data correctness, monitor/triage incidents, optimize SQL performance, apply SCD/CDC/DQ frameworks, collaborate with product owners and stakeholders, and maintain governance, security, and version-controlled code.

Design, build, and deliver production-ready Data & AI solutions on Microsoft Azure. Develop and maintain data pipelines and lakehouse architectures using Fabric, Databricks, and Azure services; implement CI/CD, optimize production workloads, and collaborate with architects, project teams, and clients.

Owner of company-wide reporting and analytics for Growth, Marketing, Product, Finance and Operations. Build and maintain dashboards, automated reports and data pipelines (dbt), ensure data quality and governance, run growth and product analyses (CAC, ROAS, LTV, retention), support A/B testing and ad-hoc decision support, leverage AI for automation, and coordinate VAs on data tasks.

The Google Cloud Data Engineer will design and implement data pipelines using Google Cloud technologies and collaborate with analysts to ensure data quality and governance.

Build and operate ingestion and transformation pipelines to turn messy insurance data into clean datasets. Design bronze/silver/fact layers, model and tune Postgres and analytical stores, define KPIs and reconciliation checks, orchestrate observable data jobs, and ensure end-to-end data quality for analytics and AI products.

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.

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 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.