Top Data Engineer Jobs in Hyderabad

The Data Engineer is responsible for optimizing data architecture and pipelines, collaborating with teams to deliver data solutions, and building analytics tools for business insights.

Design and build scalable batch and real-time data pipelines using Spark, Kafka, Java and SQL. Develop ETL/ELT frameworks, streaming solutions, data models and cloud data warehouses. Automate workflows with Airflow/DBT, monitor reliability, collaborate with Data Science and Engineering, and follow governance, security, and cost-optimization best practices.

Build and maintain large-scale data architectures and pipelines using AWS and big-data technologies. Develop ETL/streaming solutions, design data lakes, support analytics and ML use cases, implement data governance, optimize queries, and collaborate with product and data stakeholders to deliver scalable, reliable data platforms.

Design, build, and maintain scalable data pipelines and models using Big Data and cloud technologies. Ensure data quality, security, SLA adherence, and collaborate with analytics and ML teams. Monitor, optimize, and document ETL/ELT processes.

Design, build, and maintain scalable data pipelines and architectures using cloud and streaming technologies. Develop ETL/streaming workflows, optimize performance and reliability, integrate multiple data sources, ensure data governance and security, and collaborate with analytics and product teams to support data needs.

Senior Azure Data Engineer responsible for designing and implementing end-to-end data pipelines using Azure Databricks, Azure Data Factory, and PySpark. Work with Delta Lake, Spark SQL, and data warehousing concepts to build scalable ETL/ELT solutions; collaborate on analytics and Power BI integration. Availability for 2pm-11pm/12am IST shift required.

Design, build, and maintain scalable ETL/ELT data pipelines and data models. Orchestrate workflows with Apache Airflow, implement transformations with dbt, use BigQuery and GCS, ensure data quality and performance, and collaborate with analytics teams to support BI and analytics initiatives.

The Data Engineer will design and maintain AI data pipelines, manage cloud data infrastructure, and ensure data quality for analytics and machine learning operations.

The Sr GCP Data Engineer will work with cloud technologies to engineer data solutions, requiring over 5 years of experience in the field.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Build and maintain scalable ETL pipelines on GCP, transform large/disconnected datasets, automate and optimize data delivery, support stakeholders, and apply data engineering best practices including testing and release management.

Design, build, and maintain scalable ETL/ELT pipelines and microservices for marketing and product data, ingesting from ad platforms (especially Meta Ads) and event systems. Enable campaign performance tracking, lead funnel analysis, attribution, and revenue reporting. Ensure data quality, observability, governance, and documentation while collaborating with marketing, growth, and analytics to deliver actionable datasets and drive business outcomes.

Design, build, and maintain scalable ETL/ELT data pipelines on GCP/BigQuery using Python and Spark. Integrate systems (APIs, Oracle EBS), implement workflow orchestration, ensure data quality and security, monitor performance, and document processes while collaborating with analysts and business teams.

Data Engineer responsible for building and maintaining ETL pipelines, data processing workflows, and data platforms. Must have strong hands-on experience with Healthcare Revenue Cycle Management and understanding of healthcare data workflows. Role requires hybrid (onsite + offshore) work and immediate availability.

Design, build, and optimize Snowflake data models and dbt pipelines. Create Power BI reports and paginated RDLs with DAX and row-level security. Manage CI/CD with Azure DevOps, version control with Git, enforce data quality and governance, and optimize warehouse cost and performance while collaborating with business stakeholders.

Build and prepare data pipelines: mapping, cleansing, transformation, integration, and wrangling using Python and SQL. Perform feature engineering for structured and unstructured data and support API and web app deployment for data products.

Design, implement, and maintain data pipelines using Elasticsearch and data warehousing solutions, integrate data sources, and ensure data accuracy while collaborating with cross-functional teams.

As a Data Engineer, you will design and maintain systems for processing large datasets, develop data pipelines, ensure data integrity, and optimize workflows for analytics and machine learning.

As a Data Engineer, you will build scalable ETL/ELT pipelines, optimize data structures, and develop impactful Power BI solutions for stakeholders.

The Data Engineer role involves designing and maintaining ETL pipelines, optimizing data storage solutions, collaborating with teams, and ensuring data accuracy and integrity.

Design, build, and operationalize AI-enabled data pipelines and production-grade AI applications using Python and Snowflake. Prepare and transform large datasets, develop features and embeddings, support deployment and monitoring of ML/LLM models, optimize Snowflake for AI workloads, and collaborate with data science and engineering teams to deliver scalable APIs and RAG-enabled data workflows.

Seeking a Senior Data Engineer with 6+ years of experience to design and optimize data pipelines for intelligent systems, utilizing modern data platforms and cloud services.

Design, build, test and maintain large-scale data architectures and pipelines (batch and real-time) on AWS. Implement ETL/streaming solutions using Python, PySpark, Kafka, Kinesis/Firehose, DBT, and data warehouses. Build data lake solutions, enable analytics/ML tooling, integrate graph DBs, and support stakeholders with data tooling, governance, monitoring, and documentation.

The Software Engineer will manage data collection, extend cloud infrastructure, and collaborate on datasets for AI models in Speechify's data team.

Implement and maintain ETL/data‑warehousing solutions using IBM DataStage. Develop complex SQL and database solutions (Oracle/Teradata). Collaborate with team, provide technical leadership, communicate with stakeholders, and support Unix-based deployments.