At a Glance
- Tasks: Design and implement big data solutions using Databricks, guiding clients through their data challenges.
- Company: Join a leading tech firm with a focus on innovation and customer success.
- Benefits: Remote work flexibility, competitive salary, and opportunities for professional growth.
- Other info: Dynamic role with travel opportunities and a chance to work on exciting projects.
- Why this job: Make a real impact by transforming how clients leverage their data with cutting-edge technology.
- Qualifications: Experience in data engineering, coding in Python or Scala, and familiarity with cloud platforms.
The predicted salary is between 60000 - 80000 £ per year.
Location: United Kingdom Remote with occasional travel to the London office and clients' sites.
We’re hiring for multiple roles within our Professional Services team. Depending on experience and scope, this position may be offered as Senior Solutions Consultant, Resident Solutions Architect, or Senior Resident Solutions Architect. You may know this role as a Big Data Solutions Architect, Analytics Architect, Data Platform Architect, or Technical Consultant. The final title will align to your experience, technical depth, and customer-facing ownership.
As a Resident Solutions Architect in our Professional Services team you will work with clients on short to medium-term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.
The impact you will have:
- You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases.
- Work with engagement managers to scope a variety of professional services work with input from the customer.
- Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications.
- Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
- Provide an escalated level of support for customer operational issues.
- You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
- Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
What we look for:
- Extensive experience in data engineering, data platforms & analytics.
- Comfortable writing code in either Python or Scala.
- Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
- Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals.
- Familiarity with CI/CD for production deployments.
- Working knowledge of MLOps.
- Design and deployment of performant end-to-end data architectures.
- Experience with technical project delivery - managing scope and timelines.
- Documentation and white-boarding skills.
- Experience working with clients and managing conflicts.
- Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
- Travel to customers 10% of the time [Preferred] Databricks Certification but not essential.
Resident Solutions Architect (Full Stack Engineer) in London employer: Databricks
As a Resident Solutions Architect with our Professional Services team, you will thrive in a dynamic and supportive work culture that prioritises employee growth and development. With the flexibility of remote work complemented by occasional travel to our London office and client sites, you will engage in meaningful projects that leverage cutting-edge big data technologies, all while receiving comprehensive training and support to enhance your technical expertise. Join us to be part of a collaborative environment where your contributions directly impact client success and drive innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Resident Solutions Architect (Full Stack Engineer) in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with professionals on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data engineering and cloud technologies. We want to see your work in action, so make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for interviews by practising common technical questions related to big data and cloud ecosystems. We recommend doing mock interviews with friends or using online platforms to get comfortable discussing your experience and problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Resident Solutions Architect (Full Stack Engineer) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Resident Solutions Architect role. Highlight your data engineering, cloud expertise, and any relevant project delivery experience to catch our eye!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about big data and how your background makes you a perfect fit for our Professional Services team. Be genuine and let your personality come through.
Showcase Your Technical Skills:Don’t hold back on showcasing your coding skills in Python or Scala, and your experience with cloud ecosystems. We want to see how you’ve tackled challenges in the past, so include specific examples of your work with data platforms and distributed computing.
Apply Through Our Website:We encourage you to apply directly through our website! It’s the best way for us to receive your application and ensures you’re considered for the right role based on your experience. Plus, it’s super easy!
How to prepare for a job interview at Databricks
✨Know Your Tech Inside Out
Make sure you brush up on your data engineering and cloud technology skills, especially with Databricks, Apache Spark™, and the cloud ecosystems like AWS, Azure, or GCP. Be ready to discuss specific projects where you've used these technologies and how they helped solve big data challenges.
✨Showcase Your Client Interaction Skills
Since this role involves working closely with clients, prepare examples of how you've successfully managed client relationships in the past. Think about times when you resolved conflicts or provided exceptional customer service, as these stories will highlight your ability to handle customer engagements effectively.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during the interview. Brush up on coding in Python or Scala, and be prepared to solve problems on the spot. Practising coding challenges or discussing your thought process on architecture design can really set you apart.
✨Demonstrate Your Project Management Experience
Be ready to talk about your experience managing technical projects, including how you scoped work, managed timelines, and delivered results. Highlight any experience with CI/CD processes and MLOps, as these are crucial for the role. Showing that you can keep projects on track will impress the interviewers.
