Back to jobs

Data Engineering SMTS/LMTS

India - Hyderabad

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

Before you apply

New graduates
Not stated
Work authorization
Not stated
Apply at Salesforce

What you’ll work on

Full posting
  • Lead design and delivery of batch and event-driven data pipelines

  • Define patterns for ingestion, transformation, orchestration and storage

  • Build API integration components and Node.js services that expose data to apps

  • Integrate agents and MCP servers into application endpoints and data pipelines

  • Set testing, CI/CD, and SLOs for pipelines and API performance

From the employer’s posting
Lead the design, execution, and optimization of end-to-end data pipelines for batch and event-driven workloads.
Define patterns for data ingestion, transformation, orchestration, and storage using Python, SQL, dbt, Snowflake, and Airflow.
Design and maintain lightweight API integration components, Node.js services, and middleware that expose data platform capabilities to full-stack applications
Integrate autonomous agents and Model Context Protocol (MCP) servers into application endpoints and data pipelines
Establish testing strategies, CI/CD pipelines, performance tuning, and operational observability across both data pipelines and app integration services.

What you’ll bring

All qualifications

Core experience

  • Experience: Typically 10 to 14+ years of hands-on experience in Data Engineering, Software Engineering, or Platform Engineering (or equivalent demonstrated technical depth).
Qualification wording
Experience: Typically 10 to 14+ years of hands-on experience in Data Engineering, Software Engineering, or Platform Engineering (or equivalent demonstrated technical depth).

Tools in this posting

  • JavaScript
  • Python
  • SQL
  • TypeScript
  • AWS
  • dbt
  • Docker
  • Kafka
  • Kubernetes
  • Snowflake
  • Spark
  • Terraform
  • Airflow
  • Node.js
Source — Tool mentions in context
- Application Ecosystem & Integration Knowledge: - Practical experience with Node.js and TypeScript / JavaScript for building lightweight backend services, microservices, or integration layers. - Hands-on knowledge of designing and consuming REST APIs, GraphQL, webhooks, and event queues (Kafka, AWS SQS/SNS).
We are seeking a Lead Member of Technical Staff (LMTS) to serve as a primary technical execution lead across our core data platform and its application integration interfaces. This is a hands-on technical leadership role. While operating within the overarching platform architecture established by Principal Engineers, you will own the delivery of high-impact data engineering projects, build resilient pipelines, and ensure data products seamlessly plug into downstream applications, web tools, and agentic workflows. You will bring deep expertise in core data engineering (Python, Snowflake, dbt, SQL) complemented by solid working knowledge of the app development ecosystem (Node.js, APIs, microservices) to bridge data platforms with full-stack systems. You will lead project-level execution, mentor senior engineers, and translate complex requirements into production-ready software. Core Responsibilities
- Data Engineering Project Leadership & Execution: Lead the design, execution, and optimization of end-to-end data pipelines for batch and event-driven workloads. Own project-level technical delivery, write high-performance production code, and guide team members to deliver scalable data products on schedule. - Data Platform & Product Design: Define patterns for data ingestion, transformation, orchestration, and storage using Python, SQL, dbt, Snowflake, and Airflow. Establish standards for data contracts, semantic consistency, lineage, and reusable data assets to support both business analytics and AI applications. - App Ecosystem & Integration Layering: Design and maintain lightweight API integration components, Node.js services, and middleware that expose data platform capabilities to full-stack applications, web dashboards, and external enterprise platforms (Salesforce, AWS).
- Core Data Engineering Foundations: - Deep expertise in Python and advanced SQL, with a strong background in operating production data platforms. - Extensive experience with data stack technologies: dbt, Apache Airflow, Apache Spark, and Snowflake (including query optimization, performance tuning, cost management, and complex troubleshooting).
- Execution Leadership: Proven track record of leading complex data projects from requirements through architecture, deployment, and ongoing operation. - Hybrid Systems Knowledge: Ability to serve as the bridge between core data platform engineering (Python/SQL/Snowflake) and web application developer teams (Node.js/APIs). - Business & Communication Skills: Ability to translate technical implementation choices into business outcomes, work closely with product managers, and communicate effectively across engineering teams.
- Data Platform & Product Design: Define patterns for data ingestion, transformation, orchestration, and storage using Python, SQL, dbt, Snowflake, and Airflow. Establish standards for data contracts, semantic consistency, lineage, and reusable data assets to support both business analytics and AI applications. - App Ecosystem & Integration Layering: Design and maintain lightweight API integration components, Node.js services, and middleware that expose data platform capabilities to full-stack applications, web dashboards, and external enterprise platforms (Salesforce, AWS). - Agentic Architecture & Tool Integration: Implement enterprise-controlled agentic capabilities and AI-enabled workflows. Integrate autonomous agents and Model Context Protocol (MCP) servers into application endpoints and data pipelines, ensuring structured outputs, context retrieval, and clear human-agent handoffs.
- Practical experience with Node.js and TypeScript / JavaScript for building lightweight backend services, microservices, or integration layers. - Hands-on knowledge of designing and consuming REST APIs, GraphQL, webhooks, and event queues (Kafka, AWS SQS/SNS). - Understanding of web app integration patterns, API gateways, and enterprise authentication protocols (OAuth2, SSO).
- Cloud & DevOps Infrastructure: - Hands-on experience operating on cloud platforms, preferably AWS. - Familiarity with Docker, container orchestration (Kubernetes/ECS), serverless deployment (Lambda), CI/CD pipelines, and Infrastructure as Code (Terraform).
- Deep expertise in Python and advanced SQL, with a strong background in operating production data platforms. - Extensive experience with data stack technologies: dbt, Apache Airflow, Apache Spark, and Snowflake (including query optimization, performance tuning, cost management, and complex troubleshooting). - Command of distributed systems, dimensional/domain-oriented data modeling, batch/streaming patterns, and Data Mesh / data-as-a-product concepts.
- Hands-on experience operating on cloud platforms, preferably AWS. - Familiarity with Docker, container orchestration (Kubernetes/ECS), serverless deployment (Lambda), CI/CD pipelines, and Infrastructure as Code (Terraform). Qualifications

About Salesforce

Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way.

In the employer’s words · Read in context

Posting record

Report an error
Status in our records
Live
First seen by us
Oct 16, 2026 · 18 days ago
Recorded sightings
31
Last seen by us
Nov 3, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the pay range before committing time to the process.

Complete your application on salesforce.wd12.myworkdayjobs.com. The employer’s form will show what is required.

Already applied? Track this application

Job description

View original posting ↗

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

About Salesforce
 

We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good– you’ve come to the right place.

Department Overview


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

Our team partners with business and technology leaders to solve complex challenges through modern data architecture, governed data products, integrated app services, and agentic systems. We emphasize production reliability, measurable business value, and responsible automation—not experimentation without operational accountability.

Role Description: Hands On Data Lead & Systems Integrator

We are seeking a Lead Member of Technical Staff (LMTS) to serve as a primary technical execution lead across our core data platform and its application integration interfaces.

This is a hands-on technical leadership role. While operating within the overarching platform architecture established by Principal Engineers, you will own the delivery of high-impact data engineering projects, build resilient pipelines, and ensure data products seamlessly plug into downstream applications, web tools, and agentic workflows. You will bring deep expertise in core data engineering (Python, Snowflake, dbt, SQL) complemented by solid working knowledge of the app development ecosystem (Node.js, APIs, microservices) to bridge data platforms with full-stack systems. You will lead project-level execution, mentor senior engineers, and translate complex requirements into production-ready software.

Core Responsibilities

  • Data Engineering Project Leadership & Execution: Lead the design, execution, and optimization of end-to-end data pipelines for batch and event-driven workloads. Own project-level technical delivery, write high-performance production code, and guide team members to deliver scalable data products on schedule.
  • Data Platform & Product Design: Define patterns for data ingestion, transformation, orchestration, and storage using Python, SQL, dbt, Snowflake, and Airflow. Establish standards for data contracts, semantic consistency, lineage, and reusable data assets to support both business analytics and AI applications.
  • App Ecosystem & Integration Layering: Design and maintain lightweight API integration components, Node.js services, and middleware that expose data platform capabilities to full-stack applications, web dashboards, and external enterprise platforms (Salesforce, AWS).
  • Agentic Architecture & Tool Integration: Implement enterprise-controlled agentic capabilities and AI-enabled workflows. Integrate autonomous agents and Model Context Protocol (MCP) servers into application endpoints and data pipelines, ensuring structured outputs, context retrieval, and clear human-agent handoffs.
  • Verification & Production Reliability: Establish testing strategies, CI/CD pipelines, performance tuning, and operational observability across both data pipelines and app integration services. Define and enforce SLOs/SLAs for pipeline availability, data freshness, and API endpoint performance.
  • Cross-Team Leadership & Quality Standards: Conduct code and design reviews. Mentor Senior and Associate Engineers, championing engineering standards for clean code, automated testing, and documentation across both data and application interfaces.

Technical Profile

  • Core Data Engineering Foundations:
  • Deep expertise in Python and advanced SQL, with a strong background in operating production data platforms.
  • Extensive experience with data stack technologies: dbt, Apache Airflow, Apache Spark, and Snowflake (including query optimization, performance tuning, cost management, and complex troubleshooting).
  • Command of distributed systems, dimensional/domain-oriented data modeling, batch/streaming patterns, and Data Mesh / data-as-a-product concepts.
  • Application Ecosystem & Integration Knowledge:
  • Practical experience with Node.js and TypeScript / JavaScript for building lightweight backend services, microservices, or integration layers.
  • Hands-on knowledge of designing and consuming REST APIs, GraphQL, webhooks, and event queues (Kafka, AWS SQS/SNS).
  • Understanding of web app integration patterns, API gateways, and enterprise authentication protocols (OAuth2, SSO).
  • AI & Agentic Engineering:
  • Practical experience building or integrating AI-enabled workflows using frameworks like LangGraph or LangChain.
  • Working knowledge of Model Context Protocol (MCP) servers, structured outputs, context engineering, vector stores, and retrieval mechanisms.
  • Effective use of AI-native developer tools (e.g., Cursor, Codex, Claude Code) with rigorous review and testing of generated code.
  • Cloud & DevOps Infrastructure:
  • Hands-on experience operating on cloud platforms, preferably AWS.
  • Familiarity with Docker, container orchestration (Kubernetes/ECS), serverless deployment (Lambda), CI/CD pipelines, and Infrastructure as Code (Terraform).

Qualifications

  • Experience: Typically 10 to 14+ years of hands-on experience in Data Engineering, Software Engineering, or Platform Engineering (or equivalent demonstrated technical depth).
  • Execution Leadership: Proven track record of leading complex data projects from requirements through architecture, deployment, and ongoing operation.
  • Hybrid Systems Knowledge: Ability to serve as the bridge between core data platform engineering (Python/SQL/Snowflake) and web application developer teams (Node.js/APIs).
  • Business & Communication Skills: Ability to translate technical implementation choices into business outcomes, work closely with product managers, and communicate effectively across engineering teams.

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.

Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

India - Hyderabad

- Execution Leadership: Proven track record of leading complex data projects from requirements through architecture, deployment, and ongoing operation. - Hybrid Systems Knowledge: Ability to serve as the bridge between core data platform engineering (Python/SQL/Snowflake) and web application developer teams (Node.js/APIs). - Business & Communication Skills: Ability to translate technical implementation choices into business outcomes, work closely with product managers, and communicate effectively across engineering teams.
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.