Senior Data Engineer

Experience: 6+ Years

Location: Hyderabad

Role Overview:

We are looking for a skilled Data Engineer with 6+ years of experience in data integration, ETL/ELT development, cloud data warehousing, and data processing. The candidate should have robust hands-on expertise in our core technology stack and the ability to develop, maintain, and optimize scalable data pipelines.

Key Responsibilities:
Design, develop, maintain, and optimize ETL/ELT pipelines using Informatica PowerCenter, IICS, and IDMC.
Develop and optimize SQL and PL/SQL queries, stored procedures, and data processing workflows using Oracle and Microsoft SQL Server.
Build and maintain data warehouse solutions using Snowflake.
Develop cloud-based data solutions using AWS services, including EC2, S3, IAM, Lambda, and EFS.
Develop Python-based data processing solutions using Pandas, DataFrames, and NumPy.
Manage source code and version control using GitHub repositories.
Leverage AI-assisted development technologies, including LLMs, RAG, embeddings, AI agents, and prompt engineering.
Ensure data quality, performance, reliability, and maintainability across data pipelines.
Collaborate with cross-functional teams to deliver effective data engineering solutions.

Qualification Criteria:




6+ years of relevant experience in data engineering and data integration.
Robust practical knowledge of the mandatory technologies listed above.
Experience developing and troubleshooting production-grade data pipelines.
Solid analytical, problem-solving, and communication skills.
Ability to independently learn and adopt supplementary technologies as required.

Required Technical Skills:
ETL/ELT: Informatica PowerCenter, IICS, IDMC
Databases: SQL, PL/SQL, Oracle, Microsoft SQL Server
Cloud Data Warehouse: Snowflake
AWS: EC2, S3, IAM, Lambda, EFS
Programming: Python, Pandas, DataFrames, NumPy
Version Control: GitHub
AI-Assisted Development: LLMs, RAG, embeddings, agents, prompt engineering

Preferred / Supplementary Skills:
Batch Orchestration: UAC Stonebranch, Control-M, AutoSys, or Apache Airflow
Data Modeling: Star schemas, Snowflake schemas, and normalized database designs
DevOps & CI/CD: Harness, GitHub Actions, Jenkins
Containerization & Orchestration: Docker, Kubernetes
Monitoring & Observability: New Relic, Splunk, or similar tools
Domain Knowledge: Investments, banking, financial services, or BFSI experience is preferred

📌 Senior Data Engineer Hyderabad (India)
🏢 Talent Et Au Dela Management Consulting u0026 Advisory
📍 India