Description The Experience The Revenue Analytics team builds the data platforms, intelligent products, application capabilities, and AI-enabled automation that power enterprise decision-making. We combine deep engineering expertise with business context to deliver trusted, scalable systems for both human and agent-driven workflows.

We partner with business and technology leaders to solve complex challenges through up-to-date data architecture, governed data products, and agentic systems, emphasizing production reliability, measurable business value, and responsible automation.

We are seeking a Lead Member of Technical Staff (LMTS) to be a hands-on technical execution lead across our core data platform and its application integration interfaces. Working within the architecture set by Principal Engineers, you will own delivery of high-impact data engineering projects, mentor senior engineers, and turn complex requirements into production-ready software.

What You'll Actually Be Doing

- Lead design, delivery and optimization of end-to-end batch and event-driven data pipelines, writing production code and guiding the team to ship scalable data products on schedule
- Define patterns and standards for data ingestion, transformation, orchestration, storage, data contracts and lineage using Python, SQL, dbt, Snowflake and Airflow
- Build API integrations, Node.js services and middleware that connect the data platform to applications,



dashboards and enterprise platforms (Salesforce, AWS), including enterprise-controlled agentic workflows and MCP servers
- Establish testing, CI/CD, observability and SLOs/SLAs for reliability, and mentor Senior and Associate Engineers through code and design reviews

You're Our Person If...

- 10 to 14+ years in Data, Software or Platform Engineering (or equivalent depth), with a proven record of leading complex data projects from requirements through deployment and operation
- Deep expertise in Python, advanced SQL, dbt, Airflow, Spark and Snowflake (including performance tuning and cost management), plus distributed systems, data modeling and Data Mesh concepts
- Practical experience with Node.js, TypeScript/JavaScript, REST APIs, GraphQL, webhooks and event queues (Kafka, AWS SQS/SNS), including OAuth2 and SSO
- Ability to bridge data platform and web application teams, and to translate technical choices into business outcomes with product managers and engineers

Even Better If...

- Hands-on experience with AI and agentic tools such as LangGraph, LangChain, MCP servers, vector stores, and AI developer tools (Cursor, Codex, Claude Code)
- Experience operating on AWS, with Docker, Kubernetes/ECS, Lambda, CI/CD and Terraform
- Snowflake or AWS certifications
- Experience building data products that serve AI and agent-driven applications

📌 Data Engineering SMTS/LMTS (Hyderabad)
🏢 SalesForce-ad
📍 Hyderabad