Top Data Engineer Jobs in Mumbai

As an Associate Big Data Engineer at MetLife, you will support the implementation of data ingestion processes using various Big Data tools, maintain ETL code, monitor performance, and ensure data security while collaborating with cross-functional teams on data enablement solutions.

As a Senior AWS Data Engineer, you will develop and maintain data pipelines, create data models, and orchestrate workflows using tools like Amazon EMR, AWS Glue, Airflow, and SQL. Collaborating to understand data needs, you will optimize existing systems and document solutions for varied audiences while staying updated with new AWS technologies.

The Data Engineer will develop testing frameworks and automate data validation processes to ensure robust data pipelines and platform performance. Responsibilities include optimizing workflows using Apache Spark, collaborating with QA and DB specialists, and implementing monitoring solutions to resolve data processing issues.

The Data Engineer will focus on designing, automating, and optimizing ETL pipelines while ensuring integration with Snowflake and PostgreSQL, collaborating with cross-functional teams, and implementing best practices for data transformation and quality monitoring.

The GCP Data Engineer will work with Google Cloud Platform, specifically utilizing Big Query and Data Flow. Responsibilities include designing and implementing data pipelines, ensuring data quality, and collaborating with cross-functional teams to support data-driven decision-making.

As a Senior Data Engineer at Walmart, you will develop scalable solutions for extracting, transforming, and loading big data, ensuring data quality and governance, and collaborating with engineering teams globally to optimize data workflows.

The role involves developing, maintaining, and optimizing data pipelines using Matillion, SQL, and Python for the Snowflake data warehouse. It requires designing data models, collaborating with cross-functional teams, ensuring data quality, and troubleshooting ETL workflows.

The Data Engineer is responsible for analyzing complex datasets, building and maintaining data pipelines, performing data modeling, and creating scalable solutions for data insights. This role requires proficiency in Python and data processing, as well as effective collaboration with cross-functional teams to support data-driven decision-making.

As a Data Engineer, you will create data-driven solutions for leading financial institutions by collaborating with internal teams and clients. You will handle data extraction, analysis, and integration using Demyst's proprietary Python library and AWS infrastructure. Responsibilities include designing scalable code, managing production releases, and supporting clients globally.

The Data Engineer will design, develop, and maintain infrastructure for data storage and analysis, building efficient data pipelines for integration and transformation. Responsibilities include working with ETL processes, collaborating in Agile and DevOps environments, and participating in data initiatives across the organization.

As a Data Engineer, you'll be responsible for designing and implementing data pipelines using Spark and Scala while ensuring data quality, optimizing workflows, and integrating data solutions that meet business needs. You'll collaborate with teams to build efficient data processing systems and support data analysis efforts.

The Data Engineer will collaborate with various teams to implement data management and security solutions, improve telemetry services, manage data architecture, perform threat analysis, ensure compliance, conduct risk assessments, and train stakeholders. This role requires strong data engineering skills and expertise in cloud environments.

The Sr Cloud Data Engineer will lead data integration initiatives, collaborate with various stakeholders to ensure data alignment, and develop data management standards. Responsibilities include creating and reviewing data deliverables and developing and managing data pipelines and warehouse technologies.

The Data Engineer will design, build, and maintain large-scale data systems using Snowflake and AWS. Responsibilities include developing data pipelines, implementing data warehousing solutions, and collaborating to deliver data products while ensuring data quality and compliance.

As an NLP Data Engineer, you'll design, build, and maintain data pipelines for automated trading systems, manage subsystems, and engage in R&D of machine learning models to enhance execution systems.

The Data Engineer will design, implement, and manage data pipelines using Apache Airflow, migrating legacy SQL Server jobs and automating data processes related to real estate Deeds data. Responsibilities include integrating workflows with AWS Glue, ensuring data quality, and collaborating with various team members for successful project execution.

The Senior Data Engineer will build scalable data models and pipelines in Palantir Foundry, driving data ingestion, transformation, and enabling Power BI visualization. Responsibilities include normalizing data, integrating various tool datasets, automating ETL processes, and collaborating with key stakeholders for high-quality insights.