Top Data Engineer Jobs in Hyderabad

Build and optimize scalable data pipelines on Azure Databricks using Python, SQL, and Spark. Collaborate with analysts, developers, and QA to design and execute test plans, automate testing, and integrate LLM/GenAI tools for test planning and scripting while following SDLC practices.

Lead and grow a data engineering team to build scalable, secure cloud-based data platforms and ETL pipelines. Own roadmap execution, governance, observability, automation, stakeholder alignment, and platform reliability while supporting client integrations and executive reporting.

The Sr. Data Engineer at Micron will design and implement data management systems, develop ETL processes, and collaborate with cross-functional teams to prepare data for analysis.

The Data Engineer will build and maintain ELT pipelines, develop dbt models, troubleshoot issues, and document processes while collaborating with a global team.

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 and maintain data pipelines using the Azure ecosystem. Optimize streaming and batch processing with Databricks and manage Medallion Architecture. Collaborate with stakeholders to ensure data quality and support analytics use cases. Implement testing automation and best practices for governance in cloud-based systems.

Design and execute automated data quality, validation, and regression testing across ingestion, transformation, and reporting layers. Build and maintain Python/SQL-based validation frameworks, perform source-to-target reconciliation, metadata and lineage checks, analyze defects, create test data, and embed data quality checks into CI/CD pipelines. Collaborate with data engineers and analysts in Agile teams to validate Azure/Databricks data ecosystems and Power BI reporting.

Lead and deliver moderately complex data engineering initiatives: design, build, and maintain scalable, highly available data pipelines and data warehouse/analytics environments; resolve technical challenges; oversee data integration, collaborate with stakeholders, and support ML/AI pipeline development and compliance.

Lead and deliver moderately complex data engineering initiatives: design and maintain high-availability data pipelines, data models, warehouses, and analytics environments. Resolve technical challenges, oversee integration work, guide teams, ensure compliance, and collaborate to achieve enterprise data strategy and AI/ML pipeline objectives.

The Senior Test Consultant I role involves designing, building, and maintaining ETL/ELT pipelines on cloud platforms, ensuring data quality and compliance, and collaborating with various stakeholders to optimize data processing.

Lead the design and delivery of a cloud-native healthcare data platform on AWS. Architect and implement scalable batch and near-real-time pipelines, lead Apache Iceberg lakehouse engineering, build reusable ingestion/transformation/validation frameworks, drive data quality, observability, and operational excellence, review architectures, conduct code reviews, mentor engineers, and collaborate across platform, analytics, and business teams.

Design, develop, and maintain data solutions and ETL pipelines to generate, collect, process, and migrate data. Ensure data quality, implement data architecture, collaborate with stakeholders to gather requirements, and contribute to scalable data strategy and cross-functional problem solving.

Design, develop, and maintain data solutions and ETL/data pipelines. Ensure data quality, perform data modeling, integrate data across systems, and collaborate with stakeholders to translate requirements into scalable Snowflake-based deployments.

Design, build, and optimize large-scale ETL/ELT pipelines and cloud data platforms across Azure and GCP. Integrate data from multiple systems (Salesforce, NetSuite, BambooHR), optimize Spark and SQL performance, enforce governance and security, deliver data models/warehouses, and document pipelines while collaborating with stakeholders and mentoring junior engineers.

The technical lead will design and build AWS data platforms, guiding engineers, ensuring delivery excellence while collaborating with product owners and stakeholders.

The FBS Data Engineer designs and develops data solutions, ensuring data readiness for users and implementing scalable data pipelines, using various technologies while requiring limited guidance.

Lead design and development of scalable cloud data pipelines using BigQuery, Python, SQL, DBT, and Airflow. Build analytics-ready, high-performance ETL/ELT processes, enforce data quality, implement monitoring and CI/CD, collaborate with cross-functional teams, mentor junior engineers, and establish best practices and reference architectures.

Design, develop, deploy, and administer enterprise ETL solutions using SSIS. Build and optimize ETL pipelines, write advanced T-SQL, support data warehouse design and migrations, monitor and tune performance, ensure data quality/governance, provide L2/L3 support, and document processes while collaborating with BI teams.

The HR Tech Data Engineer will own the People Technology ecosystem, manage data architecture and analytics dashboards, integrate AI solutions, and ensure data compliance while partnering with senior leadership.

The Senior Snowflake Data Engineer will design and optimize scalable data solutions, develop ETL/ELT pipelines, and manage data integration on the Snowflake platform.

The Snowflake Data Engineer is responsible for designing data models, creating data integration solutions, and maintaining data pipeline architecture while leveraging Snowflake and Python. The role requires strong interpersonal skills and the ability to thrive in a client-facing environment with a focus on exceeding expectations and solving problems creatively.

Lead technical ownership of data architecture for a global data platform: design data flows and models, scale architecture via engineering and governance, establish best practices and design reviews, enable teams, and implement data quality metrics to optimize the enterprise data landscape.

The Data Engineer I will build and improve data pipelines, ensuring data quality and governance while collaborating with analysts and stakeholders.

The Staff Engineer, Data role focuses on Big Data engineering, developing ETL processes, database modeling, and machine learning systems. Requires strong analytical skills and collaboration in a dynamic team environment.

The Data Engineer will design and build data pipelines, integrate data from various sources, optimize workflows, and guide data strategies, supporting project management and best practices.