Junior SAP BASIS & HANA Consultant

HCLTech
Manchester
1 month ago
Applications closed

Related Jobs

View all jobs

Junior Data Scientist | London | SaaS Data Platform

Junior Electronics Engineer

Junior Data Engineer

Junior Data Engineer

Junior Data Analyst Apprentice (Hiring Immediately)

Junior Data Analyst Apprentice (Hiring Immediately)

Junior SAP BASIS & HANA Consultant


www.hcltech.com


Permanent / Full-Time / Remote


We are HCLTech, one of the fastest-growing large tech companies in the world and home to 225,000+ people across 60 countries, supercharging progress through industry-leading capabilities centered around Digital, Engineering and Cloud.


The driving force behind that work, our people, are diverse, creative, and passionate, raising the bar for excellence on a regular basis. We, in turn, work hard to bring out the best in them as we strive to help them find their spark and become the best version of themselves that they can be.


We are on the lookout for a highly talented and self-motivated Digital Customer Engagement Manager to join us on our journey in advancing the technological world through innovation and creativity.


Your Role & Responsibilities


We are searching for a Digital Customer Engagement Manager, who wants to make a real impact for our project with SAP. As a Digital Customer Engagement Manager, you will focuse on…

  • Supporting sales to delivery handover and customer onboarding to SAP Enterprise Cloud Services
  • Contributing to onboarding/transitioning customers to SAP ENTERPRISE CLOUD SERVICES
  • Orchestrating the overall service/project delivery according to planned scope, budget, and milestones
  • Supporting in de-escalations of critical customer situations
  • Supporting critical customer situations in conjunction with Major Incident Management (MIM), SAP Enterprise Cloud Services Customer Office teams and SAP Product Support, as applicable
  • Contributing to customer release and maintenance activities
  • Supporting customers on technical requirements throughout their lifecycle within the SAP Enterprise
  • Executing and supporting problem management and continuous improvement
  • Contributing to the liaison with different SAP stakeholders, esp. Virtual customer success partner involved in the accounts, to ensure customer success
  • Supporting in reviewing account status and analysing if account needs to be transitioned to another team, based on growth in volume or complexity of the account overtime.
  • Systematic and faster onboarding of associates: mandatory trainings documentation
  • Enabling continuous delta KTs on new topics and refresher sessions.

Qualifications & Experience


Technical Skill Set required to perform dCEM tasks

  • Technical expertise in SAP Basis area with minimum of 5 years of experience.
  • Good understanding & hands-on experience required in HANA database.
  • Experience in SAP Upgrade & Migration (OS/DB) is mandatory.
  • Experience in SaaS products (Ariba, Salesforce, C4S etc.) integration with SAP Landscape is plus.
  • Hands-on experience in any of hyper scaler (AWS/ Azure/ GCP) is needed.


Work Experiences

  • 5 - 6 years’ experience with multi-national software/IT organizations.
  • 5 years of SAP Basis S/4HANA knowledge.
  • 2+ Cloud knowledge (e.g. through Solution Management, Consulting and/or Delivery Program management).


Why Us

  • We are one of the fastest-growing large tech companies in the world, with offices in 50+ countries across the globe and 225,000 employees
  • Our company is extremely diverse with 165 nationalities represented
  • We offer the opportunity to work with colleagues across the globe
  • We offer a virtual-first work environment, promoting a good work-life integration and real flexibility
  • We are invested in your growth, offering learning and career development opportunities at every level to help you find your own unique spark
  • We offer comprehensive benefits for all employees
  • We are a certified great place to work and a top employer in 17 countries, offering a positive work environment that values employee recognition and respect

Equality & Opportunity for All


Representing 165 nationalities across the globe, we pride ourselves on being an equal opportunity employer, committed to providing equal employment opportunities to all applicants and employees regardless of race, religion, sex, color, age, national origin, pregnancy, sexual orientation, physical disability or genetic information, military or veteran status, or any other protected classification, in accordance with federal, state, and/or local law.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.