At a Glance
- Tasks: Ensure accurate data processing and drive improvements in client job progression.
- Company: Dynamic tech company located in London with a focus on data solutions.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Embrace a culture of learning and teamwork while making a real impact.
- Why this job: Join a collaborative team and enhance your skills in AWS and Databricks.
- Qualifications: 1-3 years of data processing experience and proficiency in Databricks and SQL.
The predicted salary is between 40000 - 50000 € per year.
Location: Hybrid / Monument St, London EC3R 8AJ, UK
Job type: Permanent / Full-time
Sector: IT | Data Engineer
Salary: Competitive salary
As a Data Engineer within the Production team, you will play a critical role in the swift, accurate, and secure progression of client jobs. You will be responsible for ensuring the reliability of data outputs, standardising external data, and driving process improvements that enhance our overall efficiency. This role bridges technical execution with operational excellence, requiring a proactive individual who is detail-driven, process-orientated, and eager to grow their skills within AWS and Databricks. You will work closely with Account Managers, Sales, and cross-functional teams to deliver high-quality data solutions that meet our clients' needs.
Key Responsibilities
- Data Processing & Accuracy
- Ensure the swift, accurate, and secure progression of client jobs, performing bespoke file matches, standardisation, enhancement, and deduplication of external data.
- Ensure the highest standards of data accuracy and reliability in all outputs, actively monitoring for discrepancies to reduce errors and rework over time.
- Maintain strict adherence to security, confidentiality, and data compliance protocols in all data handling.
- Technical Execution & Process Improvement
- Perform ad-hoc queries, counts, and data manipulation using Databricks, SQL, and FastStats.
- Identify, propose, and implement process improvements to enhance productivity, accuracy, and the overall efficiency of the Production team.
- Develop and maintain robust ETL (Extract, Transform, Load) logic tailored to production requirements.
- Documentation & Operations
- Create, maintain, and update all in-scope documentation for the Production Team.
- Map and document comprehensive process flows for each job type within Databricks to ensure operational resilience and knowledge sharing.
- Cross-Functional Collaboration & Customer Focus
- Collaborate effectively with Account Managers, Sales, Development, and Product teams to align data outputs with business and client expectations.
- Actively gather and respond to feedback from stakeholders to measure customer satisfaction and continuously improve the usefulness and quality of data outputs.
- Training & Development
- Take ownership of your own learning path, setting self-objectives for skill growth, particularly in AWS and Databricks ecosystems.
- Promote and implement knowledge transfer amongst team members to elevate the collective technical capability of the Production team.
Skills and Experience
- Data Processing: 1-3 years of "hands-on" data processing experience, preferably working with name and address data used for marketing.
- Technical Proficiency: Strong practical experience with Databricks and SQL.
- Data Manipulation: Deep understanding of logical data manipulation processes, including data reformats, hygiene, enhancement, and deduplication.
- Quality Assurance: Proven ability to analyze datasets, spot anomalies, and implement rigorous testing/validation to ensure data integrity.
- Tools: Good working knowledge of the Microsoft Office suite (Word, Excel, Outlook). Familiarity or experience with FastStats.
- Programming experience in Python or similar languages used for data engineering.
- Basic understanding or exposure to cloud platforms, specifically AWS.
- Knowledge of various industry suppression files.
- Experience with project management or ticketing tools (e.g., ClickUp).
Personal Attributes & Behaviours
- Self-Starter & Autonomous: Highly organised, efficient, and deadline-focused. You manage your own time effectively and take the initiative to solve problems.
- Detail-Driven & Process-Orientated: You pride yourself on quality delivery, paying meticulous attention to detail, and ensuring completeness in all the work you do.
- Agile & Curious: You have an inquisitive mind, embrace change, and are never afraid to ask questions to deepen your understanding or challenge the status quo.
- Trusted & Customer-Focused: You build strong relationships with clients and internal stakeholders by demonstrating uncompromised integrity, openness, and accountability.
- Clear Communicator: You practice open, honest, and simple communication, translating complex data concepts into understandable insights for non-technical stakeholders.
- One Team Player: You work in unity and collaboration with colleagues and clients, treating everyone as one big team working toward a shared purpose.
Data Engineer employer: Hollybank Trustees Ltd
As a Data Engineer at our London office, you will thrive in a dynamic hybrid work environment that fosters innovation and collaboration. We prioritise employee growth through continuous learning opportunities, particularly in cutting-edge technologies like AWS and Databricks, while our supportive culture encourages teamwork and open communication. Join us to be part of a forward-thinking team that values your contributions and offers a competitive salary alongside a commitment to your professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving Databricks and SQL. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common data engineering questions and scenarios. Think about how you can demonstrate your problem-solving skills and attention to detail, as these are key traits for the role.
✨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, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Databricks, SQL, and any relevant data processing skills. We want to see how your background aligns with what we’re looking for!
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 contribute to our team. Don’t forget to mention your eagerness to grow your skills in AWS and Databricks.
Showcase Your Projects:If you’ve worked on any relevant projects, make sure to include them! Whether it’s a personal project or something from a previous job, we love seeing practical examples of your data manipulation and processing skills.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at Hollybank Trustees Ltd
✨Know Your Data Inside Out
Make sure you brush up on your data processing skills, especially with Databricks and SQL. Be ready to discuss specific projects where you've handled data accuracy and manipulation, as this will show your hands-on experience.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've identified and implemented process improvements in past roles. This is key for demonstrating your proactive nature and ability to enhance efficiency, which is crucial for the Data Engineer position.
✨Communicate Clearly and Confidently
Practice explaining complex data concepts in simple terms. You’ll need to collaborate with non-technical stakeholders, so being able to communicate effectively is essential. Think about how you can translate your technical knowledge into insights that everyone can understand.
✨Demonstrate Your Curiosity and Willingness to Learn
Be prepared to discuss your learning path, particularly in AWS and Databricks. Show enthusiasm for continuous improvement and how you’ve taken ownership of your skill development in the past. This will resonate well with the team’s focus on growth.
