Top Data Engineer Jobs in Kolkata

Design, develop, and maintain cloud-based data solutions and ETL pipelines using Microsoft Azure Data Services. Ensure data quality, enable data migration and deployment across systems, optimize pipeline performance and scalability, collaborate with cross-functional teams, lead and mentor team members, and serve as an SME driving technical decisions.

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 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.

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.

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

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.

As a Data Engineer, you will design and maintain data pipelines on Databricks and AWS, focusing on ETL/ELT processes to support analytics and reporting across the organization.

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

The Looker Data Engineer will develop Looker data models, optimize reporting solutions, use Looker APIs, and work with SQL and cloud platforms.

The technical lead will design and build AWS data platforms, guiding engineers, ensuring delivery excellence while collaborating with product owners and stakeholders.

The role involves data modeling, troubleshooting complex issues, optimizing storage architectures and mentoring junior engineers while working with GCP and Python.

The Data Engineer will design, build, and maintain ETL pipelines and data products, utilizing big data technologies and ensuring efficient data architecture. Responsibilities include troubleshooting complex issues, developing scalable solutions, and managing databases and data security compliance.

The Associate Data Engineer will assist in building and maintaining data pipelines, writing SQL queries, and ensuring data quality using tools like Snowflake and Matillion.

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.

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

The Azure Data Engineer will build data pipelines and dataflows, implement security modules, and work with Azure services while supporting business requirements and data analysis.

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.

Build, operate, and scale ingestion pipelines for marketing data (ad platforms, ecommerce, analytics). Normalize and transform data into shared schemas, ensure multi-tenant reliability, observability, and security, and partner with AI/data-science teams to expose clean data for agents.

Develop and maintain PL/SQL components and complex SQL queries, translate SAS programs to SQL, tune database performance, support ETL and data migrations (batch and real-time), participate in code reviews and deployments, produce technical documentation, and troubleshoot production issues with root-cause analysis.

Design, implement, and automate Snowflake data ingestion and DBT transformation pipelines (Data Vault 2.0). Troubleshoot data operations, implement data quality monitoring, optimize platform performance, and deploy code via CI/CD while collaborating with the team.

Hands-on Big Data Engineer responsible for PySpark development on Azure Databricks, advanced SQL, and data warehouse/DWH work. Own data ingestion, preparation, integration, operationalization, and end-to-end development (coding, testing, debugging, deployment). Understand data lakes, data warehouses, and data marts. Strong communication required.