Technical Lead

We’re prioritizing Tech Leads - Data with AI exp , who have built systems & lead teams —not just explored concepts. Before you apply, a quick check — this role is hands-on and build-heavy.

If this sounds like you, we’d like to hear from you: 1️⃣ Have you built or led a system where

LLMs interact with enterprise data (APIs, warehouses, etc.) ? What was your role? 2️⃣ How have you designed

data platforms on AWS (S3, APIs, pipelines) that serve real applications, not just analytics? 3️⃣ Have you worked on

entity resolution / data matching problems? What approach did you use (rule-based, probabilistic, ML)? 4️⃣ If you were to design a

natural language query layer on top of a data platform , how would you approach accuracy and reliability? 👉 If you have clear answers to most of the above, this role is likely a strong fit.

About the Company Nuaav is a boutique technology consulting firm focused on delivering innovative, scalable, and secure data engineering and AI solutions. We partner with corporate clients to drive impactful change through specialized expertise in product engineering, data systems, AI/ML, and user experience. Our services emphasize personalized attention, agility, and quality, enabling clients to confidently transform and grow in evolving business environments.

About the Role We are seeking a hands-on

Tech Lead with 10+ years of experience (including 7+ years in data engineering) to lead a

multi-track platform build on AWS. The platform is a

modern data lakehouse that ingests data from heterogeneous sources, structures it through semantic layers, and exposes it via APIs — now evolving into an

AI-powered system with natural language querying, entity resolution, and intelligent data interactions . This role requires someone who can

own architecture and delivery end-to-end , while also driving the integration of

LLMs and emerging agentic AI patterns into enterprise data systems.

Key Responsibilities

• Own end-to-end architecture, design, and delivery across data, API, and AI tracks
• Design and implement scalable

data ingestion pipelines (native connectors + Python-based pipelines)

• Architect and maintain

lakehouse semantic layers (raw → business → application) with strong governance and lineage

• Design and build

REST APIs (read/write patterns) to serve diverse consumers and applications

• Drive

AI/LLM integration into the platform:

• Enable natural language querying over structured data
• Design data catalog / data dictionary for grounding LLM responses
• Ensure accuracy, relevance, and reliability of AI outputs
• Contribute to evolving

agentic AI workflows where AI interacts with data, APIs, and tools

• Design and implement

entity resolution frameworks (deterministic, probabilistic, ML-based)

• Establish best practices for

CI/CD, testing, deployment, and observability across data and application layers

• Collaborate with data, product, and analytics teams to translate business problems into scalable technical solutions
• Mentor engineers, conduct code reviews, and drive engineering quality

Required Skills & Experience

• 10+ years of engineering experience with

7+ years in data engineering , including leadership responsibility

• Strong experience building on

AWS (S3, Lambda, API Gateway, RDS, IAM, CodePipeline/CodeBuild, etc.)

• Deep expertise in at least one

modern data platform (Databricks, Snowflake, Dremio, Trino, Iceberg, Delta, etc.)

• Strong understanding of

lakehouse architectures, semantic layers, and query optimization

• Strong Python expertise for data pipelines, backend services, and automation
• Experience building and scaling

REST APIs (Flask, FastAPI, or similar)

• Strong SQL skills across multiple databases
• Experience with

data cataloging, metadata, and governance frameworks

• Hands-on experience with

entity resolution techniques AI / LLM (Critical Capability)

• Experience integrating

LLMs (Claude, GPT, or similar) into applications or data systems

• Understanding of

RAG (Retrieval-Augmented Generation) and grounding techniques using enterprise data

• Exposure to

agentic AI concepts (multi-step workflows, tool usage, orchestration)

• Ability to evaluate and improve

LLM output quality, latency, and reliability

• Experience designing

AI-enabled data experiences (natural language → structured queries) Preferred Skills

• Experience with

Dremio (Arctic, Sonar, reflections, virtual datasets)

• Familiarity with

vector databases, embeddings, or hybrid search

• Experience with

open table formats (Iceberg, Delta, Parquet)

• Exposure to

graph/entity resolution frameworks (Zingg, Splink, etc.)

• Knowledge of

data governance tools (Collibra, Apache Atlas, etc.)

• Experience integrating BI tools (Power BI or similar)
• Experience working in

consulting or multi-workstream delivery environments What We’re Looking For

• Engineers who can

bridge data engineering and AI systems , not treat them separately

• Strong ownership mindset — from architecture to production
• Ability to work in

ambiguity and evolving problem spaces

• Curiosity to explore and implement

AI-first system design patterns Why This Role - This is not a traditional Lead - data engineering role. You will be working at the intersection of

data platforms, backend systems, and AI/LLM-driven experiences , helping shape how enterprise systems evolve into

AI-native architectures .

Pay range and compensation package - INR 50-55 L Early Joiners or within 30 days Joiners shall be evaluated for this role

Location: Noida / Remote || Employment Type: Full-time Equal Opportunity Statement Nuaav is committed to diversity and inclusivity in the workplace. We encourage applications from individuals of all backgrounds and experiences.

if you are keen, please do share your profile with details on artee.puri@nuaav.com / hiring@nuaav.com