The world runs on data, and at Salesforce, the #1 AI CRM, we are building the intelligent platform that makes it all possible. If you are a seasoned software engineer passionate about architecting systems that handle data at a petabyte scale, we have an exceptional opportunity for you. We are actively seeking a Big Data Engineer at the Lead Member of Technical Staff (LMTS) level to join our visionary Unified Intelligence Platform (UIP) team. This role is perfect for those who thrive in a collaborative, full-stack environment and want to define the next generation of cloud-based data solutions.
This isn’t just another job posting; it’s an invitation to solve some of the most fascinating distributed systems challenges on the planet. Read on to discover if you’re the engineering mind we’re looking for.
Your Mission: Powering Intelligence with Data
The mission of the Unified Intelligence Platform (UIP) is to empower Salesforce teams to deeply understand and optimize their services and operations through data. UIP is a modern, trusted, turn-key data platform built with cutting-edge technologies. Imagine processing massive, ever-growing volumes of data daily and making it easily discoverable and analyzable for users—that’s the core of what you will be building and supporting.
The Technology Stack You’ll Master
Our platform is a sophisticated ecosystem of best-in-breed technologies. As a Big Data Engineer, you will be hands-on with a diverse and powerful suite of tools:
- Data Processing Engines: Apache Spark, Trino
- Orchestration & Workflow: Apache Airflow, DBT
- Data Storage & Format: Apache Iceberg
- Notebooks & ML: Jupyter Notebooks, Sagemaker
- Metadata Management: Open Metadata
- Deployment & Cloud: Kubernetes, across AWS and GCP environments
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Ideal Candidate Profile 🎯
Based on the job description, the ideal candidate for this software engineering role will possess the following qualities:
- A Problem Solver: Passionate about tackling big data challenges in distributed systems.
- Collaborative: Works effectively across teams to ensure customer success.
- Versatile: Adaptable and comfortable in multiple roles, from Platform and Data Engineer to DevOps.
- An Excellence Advocate: Committed to engineering excellence and delivering high-quality, maintainable products.
- A Continuous Learner: Embraces a growth mindset, always seeking to learn and improve.
- An Owner: Champions a Service Ownership model, believing in automation, monitoring, and alerting.
Key Responsibilities
In this senior capacity, the job responsibilities will be critical to the team’s success:
- Lead the architecture, design, development, and support of mission-critical data and platform services.
- Drive the development of self-service, metadata-driven data pipelines for ingesting diverse data sources into a multi-cloud platform.
- Architect robust data solutions that enhance ingestion, processing, quality, and discovery.
- Develop data frameworks to simplify recurring tasks and ensure engineering best practices.
- Establish and refine CI/CD processes for seamless deployment across cloud environments (AWS, GCP).
- Oversee and maintain key components of the tech stack, including Airflow, Spark, Trino, and Iceberg.
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Why Consider Salesforce?
Salesforce is the world’s most trusted customer relationship management (CRM) platform. They help companies unite their marketing, sales, commerce, service, and IT teams on a single, integrated platform. When you join their software engineering team, you’re not just writing code; you’re helping customers succeed everywhere.
They offer a culture of innovation, continuous learning, and ohana (family). You will be working with some of the brightest minds in the industry on problems that truly matter.
Location and Position Details
This is a full-time position with opportunities based in their offices in India.
- India – Hyderabad
- India – Bangalore
How to Apply for This Role
Ready to take on this challenge? Here’s how to tailor your application for the best chance of success:
1. Optimize Your Resume: Prominently highlight your hands-on experience with the core technologies: Spark, Trino, Airflow, Kubernetes, and cloud platforms (AWS/GCP). Quantify your achievements with metrics like data volume processed or performance improvements.
2. Prepare for the Interview Process: The process will likely assess your technical depth and architectural skills. Be ready for:
- Coding interviews focusing on algorithms and problem-solving.
- System design interviews where you’ll architect a large-scale, distributed data system.
- Deep-dive discussions on your experience with specific technologies from the stack.
- Behavioral questions about collaboration, ownership, and driving complex projects to completion.
3. Research the Platform: Understand Salesforce’s Customer 360 platform and think about how a robust internal data platform (like UIP) powers AI and insights across their products.
4. Showcase Ownership: Emphasize your experience with the full lifecycle of a service, including automation, monitoring, and operational excellence.
Ready to build the future of data? Apply for this LMTS Big Data Engineer role today and shape the future of intelligent data with Salesforce. ✨
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