Top Data Engineer Jobs in Kolkata

The Data Engineer will design, develop, and maintain ETL/ELT data pipelines, leveraging PySpark and Databricks to process large datasets, ensuring data quality, reliability, and performance optimization.

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.

Design, develop, and optimize AWS Glue ETL pipelines integrating data from S3, RDS, Redshift, and other AWS services. Transform data into analytics-ready formats, ensure data quality and security, tune performance, orchestrate workflows (Step Functions/Airflow), monitor jobs, and collaborate with analysts and stakeholders to deliver scalable data lake and warehouse solutions.

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.

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

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.

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.

The Data Engineer will translate analytical requirements into scalable data products, handle data modeling in Snowflake using dbt, manage data pipelines with Airflow, ensure data quality, and collaborate with cross-functional teams.

Design, develop, and support Azure-based data pipelines and analytics solutions. Build and maintain database objects in Azure SQL, Fabric, and Snowflake, monitor production pipelines, troubleshoot data issues, support business analytics requests, and maintain technical documentation and version control.

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.

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 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.

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.

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.

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 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.

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.