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.

Lead and deliver moderate-to-large data engineering initiatives: design, code, test, and deploy big-data pipelines and batch processing solutions. Mentor engineers, troubleshoot complex issues, ensure data quality/governance, and integrate GenAI/LLM automation. Work with Spark, Hadoop, RDBMS, cloud platforms, CI/CD, and orchestration tools to meet compliance and business objectives.

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

Assist in designing and implementing scalable data processes, develop data pipelines, support ETL from multiple sources, and enable data-driven business solutions.

The Data Engineer will create data pipelines, extract data from systems, and convert customer requirements into technical solutions, utilizing ETL tools and SQL.

Design, develop, and maintain data solutions, create data pipelines, ensure data quality, and implement ETL processes for data migration and deployment.

Design, develop, and maintain data solutions, create data pipelines, ensure data quality, and implement ETL processes for data migration.

The role requires building and optimizing pySpark applications on AWS, handling big data, and utilizing version control with Git. Strong skills in Python, PySpark, and various AWS services are needed.

The Data Engineer will design and optimize data pipelines for the enterprise data warehouse, ensuring data quality, performance, and reliability while collaborating with stakeholders to meet data requirements.

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.

Build and enhance enterprise data pipelines using Azure Databricks and related tools. Design data models, implement ETL processes, optimize Spark jobs, write Python/PySpark and SQL code, collaborate cross-functionally, and improve architecture and CI/CD automation for scalable analytics.

You will build and implement data ingestion processes using big data tools and collaborate with a team on machine learning projects. Responsibilities include performance monitoring and defining data security principles.

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.

Seeking experienced Data Engineers with 5-7 years of experience in Databricks, PySpark, and Data Fabric concepts to aid in data transformation initiatives.

The Data Engineer will develop end-to-end technical solutions, ensuring performance and scalability on cloud data platforms, while leveraging programming and data integration technologies.

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.