Top Data Engineer Jobs in Kolkata

Own and maintain analytics instrumentation and data pipelines using Segment, ensuring reliable event tracking to Mixpanel, GA4 and AppsFlyer. Use Terraform for version-controlled analytics infrastructure, monitor and audit data quality, maintain schema documentation, translate business needs into tracking, and configure mobile/web attribution and deep-linking.

Design, build, and optimize scalable data pipelines and models using Spark, Kafka, Airflow, dbt, and SQL across GCP and AWS. Ingest and normalize marketing and analytics data, ensure data quality and governance, support analytics and reporting, and collaborate with cross-functional global teams.

Design, operate, and secure scalable batch and streaming data pipelines and platforms. Own ingestion, transformation, serving, data quality, and access controls. Partner with product, risk, compliance, and InfoSec to ensure production reliability, correctness, and audit readiness for financial data.

The Data Visualization Developer will create and support dashboards in Power BI, develop SQL scripts, perform regression testing, and troubleshoot existing scripts.

As a Senior Data Engineer, you will develop and maintain data pipelines for healthcare data, ensuring data quality, reliability, and adherence to enterprise standards while collaborating with architects and stakeholders.

The Senior Data Engineer will develop data ingestion, transformation, and enrichment pipelines, ensuring data quality and reliability. Responsibilities include creating Bronze and Silver data layers, using SQL and dbt for implementation, and collaborating with architects and stakeholders to align data solutions with enterprise standards.

Lead the modeling of the Customer Data Platform, defining event taxonomy and ensuring reliable datasets for analytics, product insights, and machine learning. Collaborate with various teams to maintain data consistency and shape the architecture of the behavioral data platform.

The Senior Data Engineer will design and maintain pipelines for event data ingestion and validation, ensuring operational reliability and consistency for analytics.

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.

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.

Seeking an experienced Big Data Engineer with 5+ years in Microsoft BI Stack and 3+ years as Azure Data Integration Lead. Responsibilities include database management and SQL scripting.

As a Senior Data Engineer I, you will build data capabilities for product expansion, integrate external APIs, design robust data pipelines, and collaborate with various teams to enhance systems and practices.

As a Senior Engineer for Strategic Data Solutions, you will manage data warehousing, reporting, and analytics for internal operations and external partners. Responsibilities include collaborating with business units, providing insights, and ensuring high-quality data reporting.

The Senior Data Engineer will build and optimize data pipelines in Azure Databricks, migrate existing pipelines from Azure Synapse, and design scalable data models to support a financial services client's data platform modernization.

The Senior Data Engineer will design and build scalable data systems and analytics infrastructure, ensure data quality, and lead technical direction. Responsibilities include developing AI capabilities for the analytics platform and collaborating with teams to translate complex data into actionable insights.

As a Lead Data Engineer, you will design and manage data pipelines, develop ETL processes, and ensure data quality. Mentorship of junior engineers is also part of the role.

The Senior Data Engineer will design and maintain data pipelines, implement Medallion architecture, develop ETL/ELT processes, and improve data quality while collaborating with analysts to derive insights from data.

The Senior Data Analytics Engineer at MariaDB designs and builds data pipelines, writes SQL queries, develops internal tools, and translates data into actionable insights. They will collaborate closely with stakeholders and leverage AI tools to enhance analytics workflows.

As a Data Engineer, you'll build and monitor large-scale data pipelines, develop the DBT setup for data transformation and solve customer problems using your SQL skills.

Design, build, and optimize scalable data solutions on Azure. Manage data pipelines and ensure data quality while collaborating with stakeholders.

The Senior Data Engineer will design and optimize ETL/ELT pipelines, manage data integration, perform data validation, and support reporting solutions using various technologies.

The Snowflake Senior Data Engineer will lead projects in data engineering, utilizing Snowflake and various AWS services to optimize data workflows and storage, while also guiding the team and collaborating with stakeholders.

Develop and scale data management systems for AutoML and forecasting platforms, ensuring data reliability and implementing SLAs across pipelines.

The Senior Data Scientist & Engineer will build and manage data infrastructure, analyze product usage, build models, track metrics, run experiments, and communicate insights to guide product decisions.