At a Glance
- Tasks: Join our Production team as a Junior Data Engineer and ensure data accuracy and efficiency.
- Company: Bitrecruit, a forward-thinking tech company in Greater London.
- Benefits: Competitive salary, skill development in AWS and Databricks, and a collaborative work environment.
- Other info: Great opportunity for career growth and learning in a dynamic tech setting.
- Why this job: Make a real impact by improving data processes and collaborating with diverse teams.
- Qualifications: 1-3 years of data processing experience and strong skills in Databricks and SQL.
The predicted salary is between 30000 - 40000 £ per year.
As a Junior 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-oriented, 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; perform bespoke file matches, standardisation, enhancement, and deduplication of external data. Maintain the highest standards of data accuracy and reliability in all outputs; actively monitor 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 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 stakeholder feedback to measure customer satisfaction and continuously improve quality of data outputs.
- Training & Development: take ownership of your own learning path, set self‑objectives for skill growth in AWS and Databricks ecosystems; promote and implement knowledge transfer among team members to elevate team capability.
Essential Skills and Experience
- Data Processing: 1‑3 years of hands‑on data processing experience, preferably 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 analyse datasets, spot anomalies, and implement rigorous testing and validation to ensure data integrity.
- Tools: good working knowledge of the Microsoft Office suite (Word, Excel, Outlook).
Desirable Skills and Experience
- 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 organized, efficient, deadline‑focused; manage own time and solve problems proactively.
- Detail‑Driven & Process‑Oriented: pride in quality delivery; meticulous attention to detail; ensure completeness of work.
- Agile & Curious: inquisitive mind; embrace change; never afraid to ask questions or challenge the status quo.
- Trusted & Customer‑Focused: build strong relationships with clients and stakeholders by demonstrating integrity, openness, and accountability.
- Clear Communicator: open, honest, simple communication; translate complex data concepts into understandable insights for non‑technical stakeholders.
- One Team Player: work in unity and collaboration; treat everyone as part of one big team.
Junior Data Engineer employer: Occupop
At Bitrecruit, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to thrive. As a Junior Data Engineer in Greater London, you will benefit from extensive training opportunities in cutting-edge technologies like AWS and Databricks, while collaborating with cross-functional teams to deliver impactful data solutions. Our commitment to employee growth, coupled with a focus on innovation and process improvement, makes us an exceptional employer for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Junior Data Engineer
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like Occupop when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like Occupop.
✨Networking Through University Career Services
Don't forget to leverage your university's career services! They often have exclusive internships and networking events specifically for entry-level data science positions. This is a golden opportunity to meet recruiters from companies like Occupop.
✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through Occupop’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Junior Data Engineer
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Occupop, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Occupop aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at Occupop
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
