Data Engineer in Hyderabad, भारत

Description : Job Title : Data EngineerDepartment : Global AnalyticsReports to : Manager AI EngineeringLevel : Senior / Medior (depending on experience)Role Summary : The Data Engineer is responsible for designing, building, and operating high-quality, scalable, and reusable data services that support analytics, AI, and GenAI use cases across business https://jobeax.com/link/lJfY9qbdbDbr8V08 this role, you will design and work hands-on with data pipelines, data models, orchestration frameworks, storage layers, and observability https://jobeax.com/link/JetY84BY3FM3nVib will collaborate closely with AI Engineers, Data Scientists, Product Owners, and Platform teams to deliver reliable, well-governed, and self-service data https://jobeax.com/link/JOn0Ve3hcMQ6l4Px Responsibilities : Data Platform & Services Engineering : - Build and maintain scalable data pipelines and ingestion frameworks for batch, streaming, and event-driven data.- Develop and maintain modular data models and semantic layers optimized for analytics, BI self-service and AI use cases.- Implement and operate orchestration workflows (e.g., Databricks Workflows) and compute engines (Spark, SQL, Python).- Work with storage technologies such as Delta Lake, ADLS, feature and vector https://jobeax.com/link/1SCYiujxQTjQ5PrG Quality, Governance & Observability : - Implement data quality checks, validations, and monitoring to ensure reliability and trust in data products.- Contribute to data lineage, metadata management, and documentation.- Apply observability practices using tools such as Great Expectations or Monte Carlo.- Ensure compliance with data governance standards and regulations (e.g., GDPR) in collaboration with data governance https://jobeax.com/link/gAVXGbXg0jZfv9UH for AI & Analytics Use Cases : - Deliver curated datasets and reusable data assets for analytics, machine learning, and GenAI applications.- Build pipelines that process structured, graph, and unstructured data (e.g., text, documents, images).- Support AI Engineering teams with data preparation for embeddings, vector stores, and retrieval-augmented generation (RAG) https://jobeax.com/link/jFO3xsT2TO7UvWNa & Self-Service : - Contribute to data engineering tooling and frameworks that enable e icient development and deployment of pipelines.- Develop data pipelines using tools such as dbt and Databricks Lakeflow.- Support reuse of data services through clear documentation, data contracts, templates, and https://jobeax.com/link/K4Lnpc9YSFESO7rW & Ways of Working : - Collaborate with Data Scientists, AI Engineers, Product Owners, Business SMEs, and Platform teams.- Participate in technical design discussions, code reviews, and architecture forums.- Follow engineering best practices for version control, testing, CI/CD, and operational https://jobeax.com/link/ylLUYLmAnFRP3UAj Qualifications : - 5+ years of experience in data engineering and building production-grade data pipelines.- Strong hands-on experience with data platforms such as Databricks.- Solid knowledge of data modeling, SQL, Spark, and Python.- Experience with orchestration frameworks, data quality tooling, and observability practices.- Exposure to unstructured data processing and AI/GenAI data pipelines is a strong plus.- Experience working in a global, multi-team environment is https://jobeax.com/link/SWyCp4mkGzXdssoR in This Role Means : - Reliable, well-documented data products are available for analytics and AI use cases.- Data pipelines are scalable, cost-efficient, observable, and easy to operate.- Data engineers and AI teams can move faster using reusable patterns and self service data services.- Structured and unstructured data are effectively integrated to support advanced analytics and GenAI innovation. (ref:hirist.tech)