Full Stack Engineer

Job Description:

Role Summary

Serve as a senior full-stack engineer who builds end-to-end data products for the Decisioning practice. You own the work from data pipeline to API to user interface. Data engineering on Databricks and PySpark is the foundation of this role. On top of that, you build full-stack applications and APIs that put data and AI into the hands of media teams and clients. You are an expert in AI-assisted development using Claude Code and Cursor, and you bring a strong eye for QA and data quality to everything you ship.

Key Responsibilities

Build full-stack applications end to end: data layer, Python APIs, and React/Tailwind front ends that surface data and AI capabilities to users

Develop and maintain Python APIs (FastAPI or similar) that connect data foundations to client-facing products and agentic systems

Use Claude Code, Cursor, and other AI coding tools as a daily driver to ship features faster while maintaining quality

Where AI capability is relevant, build agentic features and tool-use patterns that automate tasks

Set the QA and data quality bar for the engineering team: write tests, build data validation frameworks, and instrument observability

Mentor mid-level engineers through code reviews, pairing, and technical guidance on full-stack practices

Collaborate with onshore leads across the engineering and craft practitioners on architecture decisions, standards, and business requirements

Contribute to reusable component libraries, claude code & cursor skills, and shared platform services that scale across clients

Partner with product designers and BI to turn static reporting into interactive, AI-powered experiences

Required Qualifications

8 - 10 years of professional software engineering experience with deep Python expertise

Demonstrated ability to build full-stack applications end to end, including React + Tailwind CSS front ends

Strong experience designing and building production APIs in Python (FastAPI, Flask, or similar)

Expert-level proficiency with AI-assisted development tools (Claude Code, Cursor, GitHub Copilot) including agentic coding patterns, context engineering, and shipping production code with these tools daily

Solid grasp of QA practices and data quality engineering: unit and integration testing, data validation, and observability

Experience with cloud infrastructure (Azure preferred) and modern deployment patterns (containers, CI/CD)

Strong written and verbal communication for collaboration across distributed onshore and offshore teams

Preferred Qualifications

Hands-on experience with LLM application development: prompt engineering, RAG, function calling, and agent frameworks (LangChain, LangGraph, CrewAI)

Background in media, advertising, or marketing technology data environments

Experience with Unity Catalog governance, including attribute-based access control and tag-driven policies

Experience building MCP servers or integrating MCP into developer workflows

Open-source contributions or public projects demonstrating full-stack or AI engineering work

Location:

DGS India - Bengaluru - Manyata N1 Block

Brand:

Merkle

Time Type:

Full time

Contract Type:

Permanent