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For Companies At a Glance
- Tasks: Design and deploy innovative data solutions using Databricks to solve real business challenges.
- Company: Join DecisionForest, a leading partner in Data & AI platforms with a collaborative spirit.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic role with excellent career advancement and continuous learning opportunities.
- Why this job: Make a tangible impact by working closely with clients on cutting-edge data projects.
- Qualifications: 4+ years in data engineering with strong skills in PySpark and SQL.
The predicted salary is between 60000 - 80000 £ per year.
Who we are
DecisionForest is a Bronze-Tier Databricks C&SI Partner, specialising in modern and scalable Data & AI platforms.
Mission
As a Forward Deployed Engineer you will work directly with client teams to design, build and deploy production solutions on Databricks. You’ll help customers solve real business problems using the Databricks platform, including data engineering, Lakehouse architecture, Unity Catalog, platform governance, workflow orchestration, performance optimisation and AI/data product enablement. You will operate close to the customer. That means joining discovery sessions, understanding current-state systems, identifying implementation gaps, building technical artefacts, shipping code, documenting patterns and helping customers adopt Databricks technologies.
Responsibilities
- Embed with customer teams to deliver production Databricks solutions.
- Build data pipelines using Databricks, PySpark, SQL, Delta Lake, and Databricks Workflows.
- Design and implement Lakehouse architecture patterns across bronze, silver and gold layers.
- Implement Unity Catalog structures, including catalogs, schemas, tables, volumes, external locations, permissions, lineage and governance patterns.
- Support migration from legacy data platforms or fragmented warehouse environments.
- Build reliable ingestion, transformation and serving layers for analytics, AI and operational use cases.
- Deliver technical artefacts for customers, including notebooks, jobs, pipelines, deployment templates, reference architectures, documentation and handover materials.
- Provide deployment support for Databricks in enterprise environments.
- Diagnose and resolve performance, reliability, cost and data quality issues.
- Work with customer stakeholders across data engineering, analytics, governance, security, architecture and leadership teams.
- Translate ambiguous customer requirements into clear technical plans.
- Identify repeatable implementation patterns and feed them back into DecisionForest delivery standards.
- Support pre-sales and post-sales activity where deep Databricks expertise is required.
- Represent DecisionForest as a specialist Databricks partner in customer environments.
What you must bring
- 4+ years of experience in data engineering, platform engineering, analytics engineering or technical consulting.
- Demonstrable experience owning at least 2 end-to-end Databricks implementations in a production environment.
- Strong production experience with PySpark and SQL.
- Experience with Databricks Lakeflow, notebooks, repos, SQL Warehouses, and cluster/serverless compute patterns.
- Solid understanding of distributed computing concepts (partitioning, shuffling, optimisation techniques).
- Practical experience with cloud data platforms on at least one major provider (ideally both Azure and AWS), including storage, networking and security basics.
- Good knowledge of data warehousing and Lakehouse patterns.
- Experience with CI/CD and modern SDLC (Git-based workflows, code reviews, deployment pipelines, infrastructure-as-code is a plus).
- Strong problem-solving skills and the ability to debug complex data issues across multiple systems (data quality, performance, reliability).
- Confident communicator, able to translate technical detail into business language for non-technical stakeholders.
- Self-driven, curious and committed to continuous learning in data engineering, cloud and analytics.
- Familiarity with data governance, security and compliance in regulated environments.
Forward Deployed Engineer - Databricks employer: DecisionForest
Contact Detail:
DecisionForest Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Forward Deployed Engineer - Databricks
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even local tech events. The more people you know, the better your chances of landing that Forward Deployed Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Databricks projects, especially those involving PySpark and SQL. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Don’t just apply anywhere—apply through our website! We love seeing candidates who are genuinely interested in joining DecisionForest. Tailor your application to highlight your experience with data engineering and cloud platforms.
✨Tip Number 4
Prepare for interviews by brushing up on your problem-solving skills. Be ready to discuss how you've tackled complex data issues in the past. Remember, confidence is key when translating technical details into business language!
We think you need these skills to ace Forward Deployed Engineer - Databricks
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Forward Deployed Engineer role. Highlight your experience with Databricks, PySpark, and SQL, and don’t forget to mention any end-to-end implementations you've owned. We want to see how your skills match our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can help our clients solve real business problems. Keep it engaging and relevant to the job description.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex data issues in the past. We love seeing candidates who can translate technical challenges into solutions that benefit the business. Make it clear how you’ve made an impact!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at DecisionForest
✨Know Your Databricks Inside Out
Make sure you brush up on your Databricks knowledge before the interview. Familiarise yourself with key concepts like Lakehouse architecture, Unity Catalog, and data pipelines using PySpark and SQL. Being able to discuss these topics confidently will show that you're ready to hit the ground running.
✨Prepare Real-World Examples
Think of specific projects where you've successfully implemented Databricks solutions. Be ready to share details about the challenges you faced, how you overcame them, and the impact your work had. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand the Customer's Perspective
Since this role involves working closely with clients, it's crucial to understand their needs and pain points. Research DecisionForest and its clients, and think about how you can help solve their business problems using Databricks. This will show that you’re not just technically skilled but also customer-focused.
✨Practice Your Communication Skills
As a Forward Deployed Engineer, you'll need to translate complex technical details into language that non-technical stakeholders can understand. Practice explaining your past projects in simple terms, focusing on the value you delivered. This will help you stand out as a confident communicator during the interview.