Top Data Engineer Jobs in Hyderabad

Design and implement data models from business requirements. Develop PL/SQL packages, procedures, and complex SQL queries. Work onsite at Dell Hyderabad; participate in face-to-face interviews and meet short notice-period constraints.

As a Senior Data Engineer, you'll design, develop, and maintain cloud data solutions, build data pipelines, ensure data quality, and collaborate with clients and teams.

As a Data Engineer, you will build and maintain data systems for drug safety AI tools, ensuring reliable data processing and storage for research teams.

Design, develop, and integrate SAP MDG solutions using ABAP, REST APIs, IDocs, and ETL. Collaborate with cross-functional teams in Agile/SCRUM, maintain code in Git, support testing and automation, and provide on-call support for master data systems.

Build and operate automated data quality checks, monitoring, alerting, and dashboards; integrate quality into data pipelines and governance tooling; automate anomaly detection and support auditors, analysts, and stewards to surface issues in near-real-time.

The Senior Data Engineer will build and optimize data pipelines in Azure Databricks, migrate existing pipelines from Azure Synapse, and design scalable data models to support a financial services client's data platform modernization.

Design, build, and optimize scalable data pipelines and models using Spark, Kafka, Airflow, dbt, and SQL across GCP and AWS. Ingest and normalize marketing and analytics data, ensure data quality and governance, support analytics and reporting, and collaborate with cross-functional global teams.

Design, operate, and secure scalable batch and streaming data pipelines and platforms. Own ingestion, transformation, serving, data quality, and access controls. Partner with product, risk, compliance, and InfoSec to ensure production reliability, correctness, and audit readiness for financial data.

Design, build, and scale cloud-native Python backend services and data-backed applications. Develop RESTful APIs, microservices, and asynchronous event-driven systems. Deploy and operate production workloads on Kubernetes and at least one public cloud (AWS or Azure). Work with cloud data warehouses (Snowflake or Databricks) and relational databases, ensuring scalable, reliable distributed systems.

Design and build production AI backend services, APIs, and data pipelines integrating LLMs and multimodal models; implement retrieval, context assembly, and grounded outputs; create evaluation and regression-testing frameworks; develop internal review tools and React operational UIs; ensure observability, monitoring, and scalable, cost-effective deployments. Own features end-to-end and collaborate with product and engineering stakeholders.

As a Data Engineer, you'll build and monitor large-scale data pipelines, develop the DBT setup for data transformation and solve customer problems using your SQL skills.

This role involves preparing proposals, understanding client requirements, assisting in technical solution design, and supporting sales teams in AI/Data projects.

Develop and scale data management systems for AutoML and forecasting platforms, ensuring data reliability and implementing SLAs across pipelines.

The Senior Data Platform Engineer will implement and maintain data platform infrastructure, optimize Databricks environments, and provide technical guidance to data engineering teams.

The Senior Data Engineer - II will design data pipelines, optimize ETL workflows, manage databases, and support Power BI reporting for business decisions.

Design and implement AI/LLM-driven data extraction and ETL pipelines, build web crawling and API integrations, implement RAG systems, mitigate LLM hallucinations, evaluate third-party tools, and collaborate with content and analytics teams to deliver high-quality, scalable data for downstream analysis.

Build, operate, and scale ingestion pipelines for marketing data (ad platforms, ecommerce, analytics). Normalize and transform data into shared schemas, ensure multi-tenant reliability, observability, and security, and partner with AI/data-science teams to expose clean data for agents.

The Backend Engineer II will build scalable backend services with Java, optimize database queries, and architect data pipelines, collaborating with teams to enhance product operations through data analysis and insights.