At a Glance
- Tasks: Design and develop scalable data platforms and pipelines for analytics and business transformation.
- Company: Join a leading independent technology and services provider in London.
- Benefits: Flexible work schedule, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with excellent career advancement opportunities.
- Why this job: Make an impact by working on innovative data solutions and mentoring junior engineers.
- Qualifications: Strong SQL skills, experience with ETL/ELT, and proficiency in Python or Scala.
The predicted salary is between 63000 - 77000 £ per year.
- Join a leading independent technology and services provider as a
- Job
Overview: The Senior Data Engineer is responsible for designing, developing, and maintaining scalable data platforms and pipelines that support analytics, reporting, and business transformation initiatives.
The role requires expertise in data engineering, cloud technologies, data modeling, performance optimization, and collaboration with cross-functional teams to deliver reliable and high-quality data solutions.
Location
London
Work Schedule
- 2 - 3 days onsite/week
- Knowledge & Experience
- Design, develop, and maintain robust ETL/ELT pipelines for structured and unstructured data.
- Build scalable data ingestion, transformation, and storage solutions using modern data engineering frameworks.
- Develop and optimize data models, data warehouses, and lakehouse architectures.
- Ensure data quality, integrity, security, and governance across data platforms.
- Collaborate with business stakeholders, data analysts, architects, and product teams to understand requirements and deliver solutions.
- Monitor and troubleshoot data pipelines, resolving performance bottlenecks and operational issues.
- Implement CI/CD, automation, and Dev Ops practices for data engineering workflows.
- Work with cloud-native services and distributed data processing technologies.
- Support data migration and modernization initiatives as part of transformation programs.
- Mentor junior engineers and contribute to technical best practices and standards.
Skills
- Strong experience in SQL and data modeling concepts.
- Hands-on experience with ETL/ELT development.
- Proficiency in Python, Scala, or Spark-based data processing.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Knowledge of Data Warehouse and Data Lake architectures.
- Experience with orchestration tools such as Airflow, ADF, or equivalent.
- Understanding of data governance, data quality, and security practices.
- Familiarity with CI/CD pipelines and version control tools.
- Preferred Skills
- Experience with Databricks, Snowflake, Redshift, Synapse, or Big Query.
- Knowledge of real-time streaming technologies such as Kafka.
- Experience in large-scale data transformation or modernization programs.
- Strong analytical and problem-solving skills.
- Excellent stakeholder communication and collaboration.
- Technical leadership and mentoring capability.
- Ability to work independently and drive delivery in a fast-paced environment.
Additional Information
Interview Process
- In Person / Teams
- #J-18808-Ljbffr
SL Transformation-Senior Data Engineer employer: Allscreens Nationwide Ltd
Allscreens Nationwide is an exceptional employer, offering a supportive team culture where employees are valued and encouraged to thrive. With access to state-of-the-art training facilities and opportunities for career progression, our Automotive Glazing Technicians in Birmingham can expect not only competitive bonuses but also the chance to work with the latest technology in the industry. Join us and be part of a company that prioritises both employee well-being and customer satisfaction.
StudySmarter Expert Advice🤫
We think this is how you could land SL Transformation-Senior Data Engineer
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We think you need these skills to ace SL Transformation-Senior Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Allscreens Nationwide Ltd. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Allscreens Nationwide Ltd
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Allscreens Nationwide Ltd!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
