Top Data Engineer Jobs in Kolkata

Designs, develops, and maintains scalable data solutions, pipelines, and ETL processes using Databricks. Ensures data quality, integrates and migrates data across systems, troubleshoots pipeline issues, and optimizes performance and reliability. The role collaborates with cross-functional teams to translate data requirements into technical solutions, documents workflows, supports data governance and security practices, and mentors junior team members.

Build, maintain, and optimize scalable batch and real-time data pipelines using PySpark, Spark, and cloud platforms. Develop ETL/ELT processes, data ingestion strategies, data lakes, and Big Data frameworks. Support data platform architecture, governance, security, performance tuning, and deployment across AWS, Azure, or GCP. Collaborate with data scientists, analysts, architects, and engineers to ensure reliable, secure, and accessible data.

Build and maintain scalable batch and real-time data pipelines, ETL/ELT processes, data lakes, and big-data processing frameworks. Use PySpark, Spark, Python, SQL, cloud platforms, and orchestration tools to ingest, transform, secure, and optimize data. Collaborate with architects, data scientists, analysts, and engineers to ensure data quality, availability, governance, and performance across high-volume workloads.

Develop and maintain data pipelines, ETL processes, and data platform solutions using Databricks. Collaborate with integration and data architects to align platform components with business requirements, troubleshoot technical issues, optimize processing performance, and support data quality and workflow efficiency. The role also involves contributing to platform design, participating in technical discussions, and mentoring junior team members.

Build, maintain, and optimize scalable batch and real-time data pipelines using PySpark, Spark, Python, SQL, and ETL/ELT tools. Design cloud-based data platforms, data lakes, ingestion strategies, and Big Data processing frameworks across AWS, Azure, or GCP. Ensure data quality, security, governance, performance, and availability while collaborating with architects, analysts, data scientists, and engineers.

Design, develop, and maintain data solutions, pipelines, data models, and ETL processes. Ensure data quality, reliability, and efficient data migration across systems. Collaborate with multiple teams, provide technical solutions, make team decisions, and serve as a subject matter expert. Monitor and troubleshoot pipeline performance while supporting analytical and operational data needs.

Build scalable Snowflake data pipelines and ETL/ELT processes across projects. Ensure data quality, security, performance, and support structured and semi-structured data for analytics. Collaborate with architects, engineers, business teams, and Team Leads to translate requirements into solutions. Contribute to CoE guidelines, frameworks, reference architectures, proof-of-concepts, and GenAI initiatives using Snowflake Cortex capabilities.

Design, develop, and maintain data solutions, pipelines, and ETL processes across systems. Ensure data quality, monitor and optimize pipeline performance, gather data requirements, and collaborate with stakeholders. The role requires independent execution, team participation, and contribution as a data engineering subject matter expert.

Design, develop, and maintain data solutions and ETL pipelines using Snowflake and related tools. Ensure data quality, lead cross-functional data strategy, mentor junior engineers, resolve complex data issues, and manage team decisions for large-scale data migrations and deployments.

Build scalable Snowflake data pipelines and ETL/ELT processes for structured and semi-structured data. Ensure data quality, security, and performance through advanced SQL, Snowpipe, Streams, Tasks, and stored procedures. Collaborate with architects, engineers, and business teams to translate requirements into solutions, support analytics and reporting, contribute to CoE guidelines and frameworks, and participate in proof-of-concept initiatives.

Build scalable, secure Snowflake data pipelines and ETL/ELT processes across projects. Develop solutions using structured and semi-structured data, optimize Snowflake performance, write advanced SQL, ensure data quality and security, and collaborate with architects, engineers, and business teams. The role also contributes to CoE guidelines, frameworks, reference architectures, proof-of-concepts, and delivery-team support while tracking emerging Snowflake and GenAI capabilities.

Build and optimize scalable data pipelines, ETL/ELT processes, data lakes, and real-time and batch processing systems. Use Databricks, Spark, PySpark, Python, cloud platforms, orchestration tools, and streaming technologies to ingest and transform data. Collaborate with architects, analysts, data scientists, and engineers to ensure data quality, security, governance, availability, and performance across large-scale data environments.

Design and lead scalable Snowflake data architectures across ingestion, storage, transformation, and access. Establish data modeling standards, security practices, performance tuning, and architecture guidelines. Mentor teams, lead proofs of concept, contribute to centers of excellence, and support presales through proposals, estimations, solutioning, and client presentations. Collaborate with integration and data architects while evaluating Snowflake and generative AI capabilities.

Design, develop, and maintain data solutions, pipelines, and ETL processes using Microsoft Azure Databricks. Ensure data quality, integration, migration, deployment, and workflow performance across systems. Lead data engineering efforts, resolve complex data challenges, coordinate with stakeholders, make team decisions, and mentor engineers while contributing to cross-team initiatives.

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.

Data Engineer responsibilities include designing and building scalable data management systems, optimizing data pipelines, managing data warehouses, and ensuring data quality and compliance.

Design and maintain scalable Snowflake data warehouses and ETL/ELT pipelines. Lead Oracle-to-Snowflake migrations, including assessment, mapping, transformation, validation, and reconciliation. Develop data models and advanced SQL workflows, optimize Snowflake performance, troubleshoot pipeline and data quality issues, and support secure, governed, monitored cloud data platforms. Collaborate with architects, analysts, application teams, and business stakeholders on enterprise data modernization.

Design, implement, and optimize graph data solutions for a supplier chain project. Responsibilities include graph modeling with LPG and RDF, Neo4j database development and query optimization, GCP data processing using BigQuery, GCS, and Dataproc, and integrating graph data with visualization tools. The role also involves schema and data design, SQL-based relational database work, performance tuning, and potentially ETL/ELT, streaming, API, and distributed systems development.

Build and operate a production data pipeline ingesting Indian MCA registration data. Responsibilities include raw-first S3 storage, resilient scraping and parsing, snapshot and diff processing, granular change events, scheduled batch jobs, alert digests, monitoring, anomaly detection, reference-table maintenance, and historical backfills. The role requires strong Python, PostgreSQL, testing, operational reliability, and production experience with uncooperative data sources.

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 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.