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Mid-level data engineer in Hyderabad at recognizable employer with broad AWS/Databricks/LLM requirements increases applicant competition.
Core data engineering skills are transferable, though enterprise domain knowledge is preferred.
Explicit 3-5 years plus mandatory AWS, Databricks, Python, Spark and API/LLM skills increases filtering.
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Own development and enhancement of high-quality data products and analytics-ready data solutions for Enabling Functions like HR, Finance, Compliance, and Procurement.
Collaborate with stakeholders and data architects to define data product strategy, build data engineering solutions, and optimize data storage, retrieval, and governance for enterprise-scale use.
Design and develop RESTful APIs and integrate LLM-powered AI capabilities (including RAG pipelines and multi-step AI agents) into enterprise workflows leveraging AWS native services and Databricks environments.
3-5 years of IT experience including developing AWS cloud-native data lakes and ecosystems with production support experience.
Proficiency in programming languages such as Python and Spark, and expertise with AWS native services (Glue Studio, Athena, Redshift, Postgres DB).
Experience with SQL databases (MySQL, PostgreSQL) and building ETL/ELT pipelines, preferably with Databricks and Delta Lake concepts.
Work Experience Required: 3-5 years in information technology including cloud data engineering; At least 1-2 years experience in an onshore-offshore delivery model.
Experienced in data engineering within enterprise enabling functions domain (HR, Finance, Compliance, Procurement) to drive data product development and governance.
Familiar with building and consuming RESTful APIs, integrating LLM APIs (OpenAI, AWS Bedrock, Anthropic Claude), and using vector databases for AI-augmented data workflows.
Comfortable working in fast-paced, dynamic global Agile/Product environments with minimal oversight and collaborating closely across data and platform teams.