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- Tasks: Join our Engineering team to build scalable data pipelines and automate data processes.
- Company: We're a dynamic company focused on digital innovation and product development.
- Benefits: Enjoy a hybrid work model with 3 days in the office and 2 days remote.
- Why this job: Be part of exciting projects, collaborate with talented teams, and enhance your data engineering skills.
- Qualifications: 4+ years as a cloud data engineer with strong Azure experience and programming skills.
- Other info: Applications will be reviewed after January 2nd, 2025.
The predicted salary is between 48000 - 84000 £ per year.
An exciting opportunity for an experienced Data Engineer to join the Engineering team working within the Digital & Product Department. Location: Chiswick (West London) Work Type: 3 days in office, 2 day from home Salary: £60k – £70k dependent on experience Full time permanent position The successful candidate will be responsible for creating the pipelines that transform data in a scalable and repeatable way. You will need to produce efficient code that automates the ingestion and cleansing of data and apply the transformations required to achieve the target data format. You will work with the Engineering and Data & Business Analytics teams to understand the source and target data requirements and use this knowledge to develop data integration solutions to achieve the necessary migrations. The Data Engineer will support the software developers, database architects and data analysts on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. You must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. DUTIES & RESPONSIBILITIES Understand, build and develop ETL and data integration solutions within Azure landscape using a wide array of technologies and data sources Analyse and organise raw data Explore ways to enhance data quality and reliability Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, etc. Work with cloud-based infrastructure (Azure) for hosting data solutions and applications Collaborate with architects, data analysts and data scientists to help meet the business goals SKILLS REQUIRED 4+ years experience as a cloud data engineer Good knowledge of the Azure data engineering stack, especially Azure Synapse and Azure Data Lake. Proven experience in development and maintenance of ETL/ELT processes within a medallion architecture. Azure synapse pipeline development and experience in writing PySpark notebooks is preferable. Good knowledge of (and preferably experience in) design and implementation of delta loads and table/column level CDC implementation. Strong experience working with relational databases (OLAP and OLTP) Programming experience in Python, PySpark and T-SQL Previous experience with Azure DevOps and understanding of CI/CD is desirable Analytical skills related to working with structured and unstructured datasets Excellent written and verbal communication skills Experience supporting and working with cross-functional teams in a dynamic environment Please Note: Swoop Recruitment are now out of office until 2nd January 2025 – we will endeavour to respond to your application as soon as possible once reviewed upon our return.
Data Engineer employer: Swoop Recruitment
Contact Detail:
Swoop Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarize yourself with the Azure data engineering stack, especially Azure Synapse and Azure Data Lake. Having hands-on experience or projects that showcase your skills in these areas will make you stand out.
✨Tip Number 2
Highlight any experience you have with ETL/ELT processes and medallion architecture. Be prepared to discuss specific projects where you've implemented these solutions effectively.
✨Tip Number 3
Showcase your programming skills in Python, PySpark, and T-SQL. Consider preparing a small project or code sample that demonstrates your proficiency in these languages.
✨Tip Number 4
Emphasize your ability to work collaboratively with cross-functional teams. Prepare examples of how you've successfully supported data initiatives in a dynamic environment.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Understand the Role: Make sure you fully understand the responsibilities and requirements of the Data Engineer position. Tailor your application to highlight your relevant experience with ETL processes, Azure technologies, and data integration solutions.
Highlight Relevant Experience: In your CV and cover letter, emphasize your 4+ years of experience as a cloud data engineer. Mention specific projects where you've developed ETL/ELT processes and worked with Azure Synapse and Azure Data Lake.
Showcase Technical Skills: Clearly list your programming skills in Python, PySpark, and T-SQL. Provide examples of how you've used these languages in previous roles, especially in relation to data transformation and automation.
Communicate Effectively: Since excellent written and verbal communication skills are required, ensure your application is well-structured and free of errors. Use clear language to describe your achievements and how they relate to the job description.
How to prepare for a job interview at Swoop Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your experience with the Azure data engineering stack, especially Azure Synapse and Azure Data Lake. Highlight specific projects where you developed ETL/ELT processes and how you utilized PySpark notebooks.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your analytical skills. Prepare examples of how you've enhanced data quality and reliability in previous roles, and be ready to discuss any internal process improvements you've implemented.
✨Collaboration is Key
Since the role involves working with cross-functional teams, be ready to share experiences where you collaborated with software developers, database architects, or data analysts. Emphasize your communication skills and how you supported team objectives.
✨Understand the Business Goals
Research the company and its business goals. Be prepared to discuss how your data integration solutions can help meet these goals, and show that you understand the importance of aligning technical work with business needs.
