Professional Services Engineer

Alteryx, Inc
1 month ago
Applications closed

Related Jobs

View all jobs

Sr Data Science Manager, Professional Services London, United Kingdom

Data Engineer

Sr. Data Scientist / Machine Learning Engineer - GenAI & LLM London, United Kingdom

▷ Urgent! Sr. Data Scientist / Machine Learning Engineer -GenAI & LLM

MLOps Engineering Manager

Head of Analytics & Data Science Decision Sciences & Machine Learning · ·

Professional Services Engineer page is loaded

Professional Services Engineer

Apply locations United Kingdom - Remote time type Full time posted on Posted 3 Days Ago job requisition id R10889

We’re looking for problem solvers, innovators, and dreamers who are searching for anything but business as usual. Like us, you’re a high performer who’s an expert at your craft, constantly challenging the status quo. You value inclusivity and want to join a culture that empowers you to show up as your authentic self. You know that success hinges on commitment, that our differences make us stronger, and that the finish line is always sweeter when the whole team crosses together.

Alteryx PSE's drive value throughout Alteryx and with our customers by effectively consulting and guiding using knowledge of software deployment and integration processes and technical skills.

As part of the Professional Services Consulting EMEA team you will be responsible for delivering services for Alteryx products, including installations, configurations, assisting with migrations from on-premises to cloud, sizing and workflow optimizations. You will be making our customers successful when they purchase professional services. With your expertise and knowledge, you will be a trusted technical advisor to our customers!

Primary Responsibilities:

  1. Support and architect enterprise-scale solutions utilizing emerging platforms and technologies.
  2. Design, guide and implement the optimal state for data and analytical architectures for customer scenarios, including Cloud and server sizing support, strategies for achieving high availability, resiliency, and disaster recovery.
  3. Provide recommended best practices on architecture, deployment, and tech stack integration.
  4. Work proactively with Technical Consultants, Analytics Consultants, and Resident Consultants to strategize on projects, cross-training and knowledge transfer.
  5. Engage with Alteryx customers as a knowledgeable Consultant.
  6. Advise customers with integration of Alteryx in their Cloud, On Prem or Hybrid ecosystems.
  7. Travel requirements up to 30%.

Preferred Qualifications:

  1. 4+ years of experience in a customer facing role, such as consulting or technical support.
  2. Proficient in Cloud resources and platforms, such as AWS, Azure, Google and VMware.
  3. Strong knowledge of Windows Server or Linux.
  4. Knowledge of data & analytic technologies and software architecture.
  5. Ability to have deep conversations with the customer Enterprise Architect to define solutions in their enterprise.
  6. Experience with software and hardware installation and configuration.
  7. Superior problem solving, organizational, decision-making written, oral, and interpersonal skills.
  8. Exceptional ability to listen, assess and document information from client.
  9. Troubleshooting techniques for parsing and dissecting log files.
  10. Experience with traditional RDBMS databases, NoSQL databases, and Hadoop.
  11. Experience with System Security, including Networking, LDAP and Active Directory.

Nice To Have Qualifications:

  1. Knowledgeable of machine learning techniques and environments, including industry leaders such as Python, R, and Spark.
  2. Prior experience with procedural languages, including Unix scripting, Java, C++, Python.
  3. Knowledge of statistical analysis, data structures, model training, scoring.
  4. Knowledgeable of emerging technology architectures built on containers and microservices and orchestrated by Kubernetes and Virtualization, such as VMWare.

#LI-SB

Find yourself checking a lot of these boxes but doubting whether you should apply? At Alteryx, we support a growth mindset for our associates through all stages of their careers. If you meet some of the requirements and you share our values, we encourage you to apply. As part of our ongoing commitment to a diverse, equitable, and inclusive workplace, we’re invested in building teams with a wide variety of backgrounds, identities, and experiences.

This position involves access to software/technology that is subject to U.S. export controls. Any job offer made will be contingent upon the applicant’s capacity to serve in compliance with U.S. export controls.

#J-18808-Ljbffr

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 AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

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

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.