Top Data Engineer Jobs in Hyderabad

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.

Develop and maintain data analytics solutions, applying statistical models and machine learning for quality engineering and operational decision-making.

The role involves developing, delivering, and supporting data engineering solutions, focusing on cloud-based systems, ETL processes, and data modeling with a requirement for extensive experience in Snowflake and Python.

As a Data Engineer, you'll design, develop, and maintain data solutions, create data pipelines, ensure data quality, and implement ETL processes.

As a Data Engineer, you will design and maintain data solutions, create pipelines, ensure data quality, and implement ETL processes across systems.

Design, develop, and maintain ETL pipelines and data solutions using Databricks. Ensure data quality, collaborate with cross-functional teams, mentor juniors, and drive team-level technical decisions to deploy and optimize data processes.

As a Data Engineer, design and maintain data solutions for data generation, create data pipelines, ensure data quality, and implement ETL processes.

The Senior Data Engineer will design and maintain scalable data pipelines, develop applications, manage CI/CD, collaborate with teams, and ensure data quality in a cloud environment.

Design, build, and maintain data pipelines and ETL processes to support healthcare payments and analytics. Ensure data quality, performance, and integration across payer, provider, and consumer datasets. Collaborate with cross-functional teams to enable reporting, data models, and scalable data infrastructure.

The Data Engineer builds and maintains the enterprise data platform, ensures reliability, designs ETL systems, and collaborates on data projects to support client needs.

The Azure Data Engineer role requires developing data engineering solutions using Azure technologies. Responsibilities include implementing data pipelines, performing data analysis, and collaborating with stakeholders on data-driven projects.

The Data Engineer designs and maintains data platforms, builds ETL processes, ensures data quality and governance, and collaborates across teams to support analytics initiatives.

The Data Engineer will develop and maintain data pipelines in the Hadoop ecosystem, perform testing, and work with cross-functional teams for data quality and integration.

The role involves architecting and implementing large-scale data pipelines, modernizing cloud-native data platforms, and mentoring junior engineers while ensuring compliance with best practices in data management.

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 scalable serverless backend systems on AWS using Lambda and API Gateway, implement event-driven architectures, integrate with AWS data stores, ensure security and fault tolerance, monitor and optimize production workloads, and collaborate on CI/CD and infrastructure automation.

Lead the design and delivery of data-driven solutions for commercial strategy in life sciences, guiding cross-functional teams, developing data products, and providing mentorship.

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.

Design and maintain scalable data pipelines using PySpark. Optimize data workflows, write SQL queries, and ensure data quality. Collaborate with teams to meet data requirements and drive initiatives to completion.

Design and maintain data pipelines using AWS and PySpark, optimize workflows, collaborate on data requirements, and ensure data quality.

The Data Engineer will design and maintain scalable pipelines using PySpark, optimize workflows, write SQL queries, and collaborate with teams to ensure data quality and integrity.

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

The role involves building scalable data applications and APIs, optimizing data architectures, and developing cloud-native solutions to drive user experience at Zoom.

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.

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.