AI Data Engineer

Client: They are a leading AI Tech Services company. With a 15K+ strong team across the APAC, they scale their platforms and capabilities to provide clients with greater agility and AI expertise across a range of Industries. Embracing a strong ecosystem of global partners, they transform technology services delivery combining AI with digital resilience to drive real business impact.

Position: AI Data Engineer
Total Experience: 5y - 8y
Relevant Experience: 5y
Location: Pune (candidate must from this location only)
Work Mode: In Office
CTC Offered: As per experience and skillsets
Joining : Immediate to 30 days
Interview process: 3 rounds - 2 technical, 1 with client 

Important: Client facing role, so excellent oral and written communication skills is a must have. Role stability of at least 2yr in an organisation is required.

Role Overview  
Seeking a AI Data Engineer with experience in data engineering, data platform engineering, or cloud-scale analytics solution delivery, with demonstrated ownership of production pipelines and platform components.

Responsibilities
- Design, build, optimize, and operate production-grade batch and streaming data pipelines using Python, SQL, and Apache Spark (PySpark) for large-scale data processing.
- Architect and implement scalable knowledge bases and Retrieval-Augmented Generation (RAG) pipelines to power downstream agentic AI use cases.
- Maintain robust production operations through comprehensive observability, error handling, performance tuning, and automated CI/CD release management.
- Enforce enterprise data architecture standards, cloud security protocols, and strict access control policies across all data and AI workflows.
- Lead discussions with engineers, architects, product owners, and business stakeholders to translate requirements into secure, maintainable platform solutions.

Requirements
- 5–8 years of experience in data engineering, data platform engineering, or cloud-scale analytics solution delivery
- Proven ability to independently design, build, optimise, and operate production-grade batch or streaming data pipelines, including orchestration, observability, error handling, 
  performance tuning, and operational support.
- Hands-on experience with Python and SQL for data transformation and validation
- Familiarity with Apache Spark (especially PySpark) and large-scale data processing concepts
- Experience with implementing knowledge base and RAG solutions for agentic AI use cases
- Self-starter with strong problem-solving skills and a keen attention to detail
- Able to work independently and lead technical discussions with engineers, architects, product owners, source-system teams, and business stakeholders to translate requirements into secure and maintainable platform solutions.
- Strong documentation and communication skills
- Should have a strong understanding of enterprise data architecture, cloud security, access control, CI/CD, release management, and production operations for data and AI platform 
  solutions.

Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.