Top Data Engineer Jobs in Kolkata

No role-specific responsibilities provided in the posting. Typically, a Unit Manager - Data Governance leads the data governance function: defining and enforcing data policies, managing data quality and metadata, coordinating stakeholders, ensuring regulatory compliance, and supervising a team to implement governance processes.

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.

The Big Data Engineer II is responsible for designing and maintaining data pipelines on cloud and on-premises, ensuring data quality and compliance, collaborating with stakeholders, and utilizing big data frameworks and cloud platforms.

The Data Engineer / Analytics Engineer will build scalable data models and pipelines using dbt and Snowflake while collaborating with stakeholders and engineers.

The Data Engineer is responsible for implementing business logic in the Data Warehouse, designing ETL pipelines, optimizing data loading processes, and collaborating with stakeholders to improve data architecture.

Data Engineer focusing on AI/ML to design data pipelines, integrate ML models, and maintain data infrastructure for analytics and business intelligence, collaborating with cross-functional teams and mentoring junior engineers.

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

The Snowflake Data Engineer will develop and manage large-scale data pipelines, collaborate with stakeholders, and optimize data engineering solutions using Snowflake.

Assist in designing and implementing scalable data processes, develop data pipelines, support ETL from multiple sources, and enable data-driven business solutions.

Seeking experienced Data Engineers with 5-7 years of experience in Databricks, PySpark, and Data Fabric concepts to aid in data transformation initiatives.

The Data Engineer will design, build, and maintain ETL/ELT pipelines, ensuring data quality, security, and compliance while collaborating across multiple teams.

Design and build data infrastructure and architecture, optimize data processes, implement ELT applications, and develop high-quality data pipelines for clients.

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.

The IT Data Engineer will develop and optimize ETL/ELT workflows, implement Lakehouse architecture, integrate Azure services, and oversee data governance practices, while supporting CI/CD and collaborating with stakeholders.

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.

The Data Engineer will build and maintain ETL/ELT pipelines, implement automated data quality checks, optimize data storage, and create interactive visualizations. They will manage CI/CD pipelines and deliver production-ready data solutions.

The Data Engineer will design and maintain ETL pipelines, optimize data models, ensure data quality, and transform HR data into actionable insights for workforce decisions.

The Data Engineer designs and implements scalable data processes, manages data pipelines, assists data scientists, and supports the organization's cloud strategy while leading junior engineers.

The Data Engineer designs, develops, and maintains data pipelines and infrastructure, ensuring data accuracy and accessibility while collaborating with data teams.

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.

Design and develop scalable data pipelines using PySpark and Databricks, focusing on data ingestion, transformation, validation, and performance optimization.

The Lead Data Engineer will design and build scalable data pipelines on Databricks, develop ETL/ELT pipelines with PySpark, and mentor engineering teams for data transformation and analytics.

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.

The role involves designing, developing, and maintaining large scale data engineering solutions while collaborating with stakeholders on data governance and analytics.

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