Senior Data Engineer Big Data & GenAI

Location: Chennai

Experience: 24 Years

Employment Type: Full-Time

Role Overview:

We are looking for a highly skilled and hands-on Data Engineer with strong expertise in Big Data technologies, distributed data processing, and backend engineering. The ideal candidate should have practical experience in building scalable batch and real-time data pipelines using frameworks such as PySpark, Kafka, and streaming platforms. The candidate should also possess strong Python programming skills and experience building APIs/microservices using modern backend frameworks. This role is best suited for engineers who enjoy solving large-scale data engineering problems and working closely with AI/GenAI-driven applications. We are specifically looking for candidates with strong hands-on coding and distributed systems experience, and not candidates whose experience is predominantly limited to traditional ETL tools, low-code cloud pipelines, or Snowflake-centric workflows.

Key Responsibilities:

- Design, develop, and optimize scalable batch and streaming data pipelines.

- Build large-scale distributed data processing systems using PySpark.

- Develop real-time streaming solutions using Kafka and/or Apache Flink.

- Build and maintain APIs and backend services using Python-based microservice frameworks.

- Work with structured and semi-structured datasets across multiple storage systems.

- Optimize pipeline performance, scalability, and fault tolerance.

- Collaborate with AI/ML and GenAI teams to support LLM and RAG-based applications.

- Participate in architecture discussions, debugging, code reviews, and production deployments.

- Ensure reliability, monitoring, and maintainability of data engineering systems.

Mandatory Skills:

- Strong hands-on experience with PySpark and distributed data processing (must-have).

- Strong programming expertise in Python.

- Hands-on experience building APIs and backend services using:

1. Flask

2. FastAPI

3. Or similar microservice frameworks

- Good understanding of Big Data ecosystem and streaming architectures.

- Experience with:

1. Apache Kafka

2. Apache Flink (preferred)

3. PostgreSQL

- Experience building end-to-end batch and real-time data engineering pipelines.

- Good understanding of scalable system design, partitioning, optimization, and distributed processing concepts.

- Understanding of microservices architecture and API integrations.

- Experience working in Linux-based environments.

- Strong analytical and problem-solving skills.

GenAI / AI Engineering Expectations:

- Candidates should also have practical exposure to modern GenAI concepts and tools, including:

1. Working knowledge of LLMs and prompt engineering.

2. Understanding of RAG (Retrieval-Augmented Generation) concepts.

3. Experience using GenAI frameworks/tools such as:

i. LangChain

ii. LlamaIndex (good to have)

- Exposure to vector databases, embeddings, or AI-assisted workflows is a plus.

Good to Have / Bonus Skills:

- Experience with QuestDB.

- Exposure to real-time analytics and streaming systems.

- Understanding of distributed systems internals.

- Experience with Docker/containerization and deployment workflows.

- Familiarity with monitoring and logging frameworks.

- Knowledge of cloud platforms is an added advantage.

Important Note:

This role is focused on core data engineering, distributed systems, and backend engineering. Candidates with predominantly:

1. Snowflake-only experience

2. Low-code ETL pipeline development

3. Pure cloud ETL orchestration backgrounds

may not be the right fit for this requirement unless they also possess strong hands-on Big Data engineering and programming experience.

Preferred Candidate Profile:

- Strong ownership mindset and problem-solving ability.

- Comfortable working independently on complex engineering problems.

- Ability to work in fast-paced product/research-oriented environments.

- Passion for learning modern AI and data technologies.

- Good communication and collaboration skills.