Top Data Engineer Jobs in Kolkata

Design, build, and maintain scalable Snowflake data pipelines and ETL/ELT processes. Ensure data quality, performance tuning, and security using Snowpipe, Streams, Tasks, and stored procedures. Collaborate with architects, engineers, and business teams, contribute to CoE guidelines, and support POCs. Mentor delivery teams and stay current on Snowflake and GenAI capabilities.

Design, build, and maintain Snowflake-based data architectures and ETL pipelines. Lead Snowflake solution design, data modeling, performance tuning, security, mentoring, presales, and POCs across projects.

Design, build, and maintain scalable ETL/ELT data pipelines and data lakes using Databricks, Spark/PySpark, cloud platforms, and orchestration tools. Optimize Spark jobs, support real-time streaming (Kafka), ensure data quality, and collaborate with architects, data scientists, and engineers to implement secure, governed data platform solutions.

Design, develop, and maintain Snowflake-based data architectures and ETL pipelines. Lead Snowflake solutions for ingestion, storage, transformation, and access; define data modeling standards; mentor teams; drive POCs, presales, and best practices; ensure performance, security, and integration across systems.

Build, maintain, and optimize scalable ETL/ELT and streaming data pipelines using Databricks, Spark/PySpark and cloud platforms. Design data platform components, ensure data quality, support data lakes, orchestration, CI/CD, and collaborate with data stakeholders to ensure secure, performant data solutions.

Build and maintain scalable Snowflake data pipelines and ETL/ELT processes, ensure data quality and security, tune performance, write advanced SQL, collaborate with architects and teams, support CoE initiatives, and contribute to POCs/POVs across projects.

Design, build, and maintain scalable ETL/ELT data pipelines and data lakes using Databricks, Spark/PySpark, and cloud platforms. Support real-time streaming (Kafka), data quality, performance tuning, governance, and cross-team integration while enabling data scientists and analysts.

Design, implement and maintain Snowflake-based data architectures and ETL pipelines. Lead ingestion, storage, transformation and access best practices, mentor teams, support presales, run POCs, and ensure data quality, security, performance tuning and governance across projects.

Design, build and maintain scalable Snowflake data pipelines and ETL/ELT processes. Ensure data quality, performance tuning, and security. Collaborate with architects and business teams, support CoE initiatives, and contribute to GenAI POVs/POCs using Snowflake and Cortex LLM capabilities.

Design, build, and maintain scalable ETL/ELT data pipelines and data lakes using Databricks, Spark, and cloud platforms. Ensure data quality, support real-time and batch processing, optimize Spark performance, and collaborate with architects, data scientists, and engineers to deploy secure, governed data solutions.

Design, develop, and maintain data solutions and ETL pipelines using Databricks. Ensure data quality, optimize pipeline performance, collaborate with stakeholders to gather requirements, and support deployment and migration of data across systems. Act as an independent contributor and subject-matter expert.

Design, build, and maintain scalable ETL/ELT data pipelines and data lakes using Databricks and Spark. Implement batch and real-time streaming ingestion, ensure data quality and governance, optimize Spark job performance, collaborate with architects and data scientists, and support cloud deployments and CI/CD practices.

Design and lead Snowflake architectures and data solutions, build ETL/data pipelines, ensure data quality and security, mentor teams, drive CoE initiatives, support presales and run POCs/POVs including GenAI integrations leveraging Snowflake Cortex and related tools.

Design, build and maintain scalable Snowflake data pipelines and ETL/ELT processes. Ensure data quality, performance tuning, advanced SQL, and security. Support CoE initiatives, collaborate with architects and teams, and enable delivery through best practices and POCs.

Design, develop, and maintain data solutions and ETL/data pipelines. Ensure data quality and governance, optimize data models and warehouses, troubleshoot pipelines, and lead teams to deliver cross-functional data solutions.

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, 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.

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, 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.