Salesforce Big Data Engineer Hiring 2025
Introduction
Overview of the IT Job Market
The field of Big Data Engineering is witnessing unparalleled growth, emerging as the linchpin of contemporary enterprise decision-making. With companies relying more and more on data-driven insights to outcompete, the need for engineers who can design, manage, and grow data infrastructure has exploded. In India, tech hotspots such as Hyderabad and Bangalore are right in the middle of this revolution, home to the headquarters and large development centers of international technology leaders. Getting a job in this field, particularly at an innovative company like Salesforce, is a deliberate career choice that promises stability, enormous learning opportunities, and visibility to pioneering technologies in the cloud data world.
Scope & Growth Opportunities
A Big Data Engineer job at Salesforce is not only a career; it’s the gateway to the realm of large-scale data processing. Salesforce, the #1 CRM platform in the world, is built on a volcano of customer information. This job places you at the center of managing that information, gaining priceless experience that is extremely valuable throughout the tech sector. The career path is amazing. You can go from being an individual contributor to a Lead/Architect role, focusing on technologies such as real-time data streaming, machine learning infrastructure, or cloud data warehousing. In addition, Salesforce has its own culture of internal mobility (or the “Flow”) where engineers can shift between teams and even locations, contributing to various products in its vast suite such as Tableau, MuleSoft, and Slack.
Job Role Overview
About the Position: Software Engineering LMTS/ Big Data Engineer
The name “Software Engineering LMTS” is an acronym for Lead Member of Technical Staff, which is a senior individual contributor role at Salesforce. But the advertisement is welcome both for freshers and experienced candidates, which means that Salesforce is compiling a team with a combination of skill, where veteran engineers will guide new entrants. The central role is that of a Big Data Engineer. The job of a Big Data Engineer is to plan, build, test, and support the overall architecture of big data processing systems. These infrastructure systems form the backbone of analytics, reporting, and data feeding into machine learning models that power Salesforce’s smart CRM capabilities.
Key Responsibilities
A Big Data Engineer at Salesforce is normally responsible for the following:
· Architecting Data Solutions: Building scalable, durable, and efficient data pipelines to ingest, process, and store billions of structured and unstructured data from varied sources.
· Data Processing & Transformation: Creating and keeping up-to-date ETL/ELT processes with Big Data technologies to process, aggregate, and transform raw data into data formats that are easily consumable by data scientists and analysts.
· Platform Development: Creating and refining the underlying data platforms and frameworks that data teams across the company will utilize.
· Maintaining Data Quality & Reliability: Establishing processes and monitoring to verify the accuracy, consistency, and availability of data. Troubleshooting and solving data-related problems.
· Performance Tuning: Optimizing data pipelines and queries for performance and cost-effectiveness continuously, particularly in a cloud environment.
· Collaboration: Working together with Data Scientists, Analysts, Product Managers, and other software engineers to get an understanding of the requirements of the data and provide effective solutions.
· Operational Excellence: Developing automated monitoring, alerting, and recovery processes to maintain the health of data systems.
Essential Qualifications
Educational Background
Salesforce seeks applicants with a good academic background in computer science or relevant quantitative disciplines.
· A Bachelor’s or Master’s Degree (B.Tech/B.E./M.Tech/M.S.) in Computer Science, Information Technology, Data Science, or a relevant field from an established university.
· Preferred Streams: A clear preference is shown for candidates having graduation degrees with a high emphasis on algorithms, distributed systems, and data management.
Their graduation year:
Candidates from the passing-out batches of 2023, 2024, or 2025 are generally considered for new graduate positions.
Preferred Degrees / Certifications
Although not always required, these can really make your application stand out:
· Advanced Degrees: Master’s degree with specific specializations in Big Data, Cloud Computing, or Distributed Systems is a major plus.
· Salesforce Certifications: Certifications such as Tableau Desktop Specialist or Salesforce Certified Data Architect demonstrate domain-driven effort.
· Cloud Certifications: A foundation or associate-level AWS certification (e.g., AWS Certified Cloud Practitioner, AWS Certified Data Analytics – Specialty) or the equivalent from a similar cloud platform is greatly appreciated.
Skills Required
Salesforce Big Data Engineer Hiring 2025
Technical Skills (Programming, Tools, Platforms)
In order to be excellent as a Big Data Engineer, a candidate should have or be able to learn very fast:
· Programming Languages: Java, Scala, or Python should have expert-level proficiency. SQL is not negotiable.
· Big Data Frameworks: Practical knowledge or strong theoretical understanding of Apache Spark (central for distributed computing) and tools of the Hadoop ecosystem (such as HDFS, Hive, HBase).
· Data Processing & ETL: Familiarity with ETL frameworks and tools such as Apache Kafka (for real-time streaming), Apache Airflow (for workflow management), and dbt (data build tool).
· Cloud Data Platforms: AWS (Amazon Web Services) proficiency is essential, as Salesforce operates on AWS. Major services are S3, EC2, EMR, Glue, Redshift, and IAM.
· Databases: Good knowledge of both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., Cassandra, DynamoDB) databases.
· DevOps & Tools: Knowing version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes) is a big plus.
Soft Skills (Communication, Problem-solving)
· Analytical & Problem-Solving Mindset: Ability to break down complicated, ambiguous data issues and craft sound, scalable solutions.
· Collaboration & Teamwork: Mastering working in cross-functional teams. Salesforce’s culture, founded on the idea of “Ohana” (family), is about trust and collaboration.
· Communication Skills: The capacity to explain technical issues and solutions in clear terms both to technical counterparts and non-technical stakeholders.
· Growth Mindset: Displayed enthusiasm for ongoing learning and evolving with the fast-changing Big Data environment.
· Attention to Detail: Meticulousness in maintaining data correctness and pipeline dependability.
Eligibility Criteria
· Work Experience: This particular listing is available to any spectrum of candidates, from freshers to experienced professionals. Using the term “LMTS” implies there are positions available for highly experienced persons, yet the fact that it also lists freshers means that there is an eagerness to recruit and train top new talent.
· Location: The position is located in Hyderabad or Bangalore, India. The applicants should be ready to work remotely from these locations, possibly under a hybrid work arrangement.
Job Location & Work Mode
· Job Location: The main locations for this position are Hyderabad, Telangana and Bangalore, Karnataka. Both cities are top IT centers in India, featuring state-of-the-art Salesforce offices with great amenities.
· Work Mode: Salesforce has a flexible hybrid working model. Employees are generally required to work from the office for a predetermined number of days per week (e.g., 1-3 days) to support collaboration and culture, with the freedom to work from home for the balance.
Salary & Benefits
Expected CTC / Range
Salary for a Big Data Engineer position at Salesforce is very competitive and depends on experience.
· For Freshers: The anticipated Total Annual Compensation (CTC) for a fresh graduate in this position can vary between ₹12 Lakhs to ₹18 Lakhs per year. It involves base salary, joining allowance, and stock units (RSUs).
· For Experienced Hires (LMTS Level): Salaries for experienced personnel could be much higher, from ₹25 Lakhs to ₹45 Lakhs+ per year, depending greatly on the years of experience in the field and interview performance.
Perks & Other Benefits
Salesforce is always considered a top workplace and recognized as having great benefits:
· Health & Wellness: Full health insurance for employees and their families, including parents. Wellness reimbursement programs.
· Financial Benefits: Employee Stock Purchase Plan (ESPP) to purchase company stock at a discounted rate, retirement planning opportunities.
· Time Off: Plenty of paid time off, volunteer time off (VTO), parental leave, and sabbaticals for long-term employees.
· Learning & Development: $5,000+ per year allowance for ongoing education, certifications, and professional development.
· Special Benefits: Top-notch office facilities, complimentary food and snacks, employee resource groups (Ohana Groups), and a significant emphasis on equality and sustainability.
Application Process
Application Steps (Step-by-Step)
Applying via the official Salesforce careers website is essential.
- Click the Official Application Link: Utilize the link provided to get your application submitted properly.
· Official Application Link: Apply for Software Engineering LMTS – Big Data Engineer at Salesforce - Create/Login to Your Account: Create a profile on the Salesforce Careers website.
- Upload Your Resume: Customize your resume to emphasize Big Data skills (Spark, AWS, Java/Python/Scala). The system will also scan it to auto-fill the application.
- Complete the Application Form: Enter all the required details carefully, such as education, experience, and skills.
- Submit and Confirm: Double-check all the information and apply. Wait for an email confirmation.
Selection Process
Carefully crafted to be comprehensive and test both technical proficiency and cultural alignment.
- Application Review: Interviewers filter applications for key words, skills, education, and project experience.
- Online Assessment (OA): Potentially a coding and problem-solving exercise based on data structures, algorithms, and possibly SQL or data manipulation questions.
- Technical Phone Screen(s): One or more rounds with senior engineers focusing on coding challenges (likely in Java/Scala/Python), SQL queries, and fundamental concepts of distributed systems.
- Virtual On-Site Interview Loop (The Core): This final stage typically consists of 4-5 rounds:
· Coding Rounds: Deep-dive coding problems focusing on efficiency and scalability.
· System Design Round: Large-scale data system design (e.g., “Design a data pipeline for processing real-time user clickstream data”).
· Data Modeling Round: An SQL and database design round.
· Behavioral Round: Questions derived from Salesforce’s guiding values (Trust, Customer Success, Innovation, Equality). - Hiring Committee & Offer: The feedback of all the interviewers is compiled by a hiring committee. The shortlisted candidates are called by the recruiter and a verbal offer is made to them, followed by a written offer letter in detail.
Tips to Crack IT Jobs
Resume Preparation
· Big Data tailored: Emphasize Big Data-related projects and skills: mention Spark, Hadoop, Kafka, AWS, and size of the data you’ve handled (e.g., “Processed 1TB+ dataset using Spark on EMR”).
· Put numbers to impact: Use numerical values. “Optimized a Spark job, shortening runtime by 40% and saving 20% on cloud expenses” is strong.
· Showcase Projects: List 1-2 notable data engineering projects on your resume with references to your GitHub repository.
Interview Preparation
· Master Core Concepts: Reinforce your knowledge of Distributed Systems concepts (sharding, replication, consistency) and Big Data architectures (Lambda, Kappa).
· Practice Coding & SQL: Practice solving LeetCode problems (Medium/Hard problems) and sites like StrataScratch for SQL and data-related problems.
· System Design Prep: Refer to resources such as “Designing Data-Intensive Applications” by Martin Kleppmann and bytebytego system design course.
· Behavioral Prep: Ready stories illustrating how you live Salesforce’s values. Utilize the STAR approach to answers.
Upskilling Platforms
· Big Data Tech: Coursera (“Big Data Specialization” by UCSD), edX.
· AWS: AWS Training and Certification portal, A Cloud Guru.
· Practice: LeetCode, HackerRank, StrataScratch.
Conclusion
Why this Job is a Good Opportunity
Big Data Engineer at Salesforce is a career launching or advancing opportunity in one of the highest demand areas in tech. You will be joining at the interface of cloud computing and big data, tackling hard problems at a scale that few businesses can provide. The “Ohana” culture, constant learning, and innovation environment make Salesforce an incredible place to develop technically and personally.
Encouragement & Career Growth Scope
If you are passionate about data and problem-solving, this job is perfect for you. Don’t be discouraged by the “LMTS” label; Salesforce’s openness to hiring freshers speaks volumes about its commitment to young talent. Study hard, concentrate on learning a good basic understanding of big data concepts, and be sure to give it your best shot. This might be your first step towards being a world-class data engineer.
Disclaimer: This blog is provided for information purposes only. Any specific information available concerning the job position, eligibility, compensation, and procedure is as per the publicly posted job announcement and industry norms. These are liable to be changed at Salesforce, Inc.’s discretion alone. Always check the official Salesforce Careers website and your official offer letter for the most precise and authoritative information.
