Top Data Engineer Jobs in Kolkata

Design, build, and operate scalable ETL/ELT pipelines using PySpark and AWS data services. Orchestrate workflows with Apache Airflow, implement AWS Glue jobs and Data Catalog, manage Lake Formation permissions, publish datasets for BI, and deliver QuickSight visualizations while ensuring data quality and performance.

As a Data Engineer, you will build data pipelines, design data models, and deploy Data Ops, collaborating with multiple teams to enhance product offerings.

Design, develop, and maintain data solutions and ETL pipelines using Databricks. Ensure data quality, optimize workflows, collaborate with cross-functional teams, and resolve data-related challenges to meet business needs.

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.

Design and deliver end-to-end cloud data solutions, lead discovery and technical design, build and optimize scalable ETL/ELT and real-time pipelines, implement CI/CD and IaC, develop observability and data quality, perform performance tuning and root-cause analysis, and advise customers while contributing to automation and thought leadership.

Maintain and monitor web scraping configurations, ingest and transform scraped data into the data lake, detect and resolve pipeline issues, produce stakeholder reports, and build scalable ETL pipelines and data architectures to support analytics.

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

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 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 designing and maintaining data pipelines, ensuring data quality, and integrating data for analysis using advanced technologies such as Snowflake and AWS.

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

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

Design, build, and optimize scalable ELT/ETL pipelines on Azure using ADF and Databricks, integrate data into Snowflake, implement Data Vault 2.0 modelling, ensure data quality and performance, and collaborate with stakeholders and analytics teams to maintain production workflows.

Design, build, and maintain scalable batch and real-time data pipelines on Azure using Kafka, Spark, Databricks and ADF. Optimize Snowflake models and SQL, process structured and semi-structured data, ensure data quality, performance, and collaborate with cross-functional teams.

The Senior Data Engineer will design, build, and maintain scalable data processing systems, optimizing data pipelines, and collaborating on data architecture.

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.