At a Glance
- Tasks: Design and deliver scalable data solutions using Big Data technologies.
- Company: Join a renowned financial services organisation with a focus on innovation.
- Benefits: Flexible working options and opportunities for professional growth.
- Other info: Dynamic role with a focus on real-time data processing and analytics.
- Why this job: Make an impact by modernising data platforms and optimising processes.
- Qualifications: Expertise in Big Data, Hadoop, and data engineering required.
The predicted salary is between 36000 - 60000 £ per year.
Are you the right applicant for this opportunity? Find out by reading through the role overview below.
Your new company: Working for a renowned financial services organisation.
Your new role: We're looking for a Senior Data Engineer to design and deliver scalable on-prem, high-quality data solutions for low/high-level data platforms that power analytical and business insights. This is a hands-on role suited to someone with strong data engineering and big data expertise, ideally gained within financial services. Joining a leading commodities, metals, trading, and exchange group, you will support a strategic metals initiative focused on reducing on-prem platform costs and modernising legacy ETL processes. You'll help design and build a new on-prem data platform aligned to the metals strategy while developing and maintaining scalable data pipelines and analytics infrastructure. Using Hadoop, Big Data, and Spark technologies, you will ensure data quality through automated validation, monitoring, and testing. You will also enable seamless integration across data warehouses and data lakes, contributing to a robust, scalable, and resilient enterprise data ecosystem.
What you'll need to succeed:
- Vast Data Engineering expertise with Big Data technologies.
- Experience designing and building on-prem data platforms, from high-level architecture to detailed technical design.
- Hands-on experience configuring multi-node Hadoop clusters, including resource management, security, and performance tuning.
- Strong Big Data engineering background using Apache Airflow, Spark, dbt, Kafka, and Hadoop ecosystem tools.
- Knowledge of RDBMS systems (PostgreSQL, SQL Server) and familiarity with NoSQL/distributed databases such as MongoDB.
- Proven delivery of streaming pipelines and real-time data processing solutions.
- Improved job efficiency and reduced runtimes through Apache Spark optimisation and development.
- Some experience with containerisation (Docker, Kubernetes) and CI/CD pipelines.
- Delivered streaming pipelines and real-time data processing solutions.
- Experience replacing legacy ETL tools (e.g., Informatica) with modern data engineering pipelines and platform builds.
- Proven background working within financial services environments.
What you'll get in return: Flexible working options available.
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
Senior Data Engineer Big Data/ Hadoop/ Spark employer: Hays Specialist Recruitment Limited
As a leading financial services organisation, we pride ourselves on fostering a dynamic and inclusive work culture that prioritises employee growth and innovation. Our commitment to flexible working options and the opportunity to engage in cutting-edge projects within the commodities and trading sectors make us an exceptional employer for those looking to advance their careers in data engineering. Join us to be part of a forward-thinking team dedicated to modernising data solutions and driving impactful business insights.
Contact Details:
Hays Specialist Recruitment Limited Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer Big Data/ Hadoop/ Spark
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We think you need these skills to ace Senior Data Engineer Big Data/ Hadoop/ Spark
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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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