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- Tasks: Build and support innovative data products with a collaborative team.
- Company: Join a forward-thinking company focused on data and AI solutions.
- Benefits: Enjoy flexible working, generous holiday, health perks, and tech discounts.
- Other info: Inclusive workplace with excellent career growth and well-being initiatives.
- Why this job: Make an impact in the exciting world of data and machine learning.
- Qualifications: Strong Python, SQL skills, and experience with cloud data platforms required.
The predicted salary is between 54000 - 81000 ÂŁ per year.
We are currently recruiting for a Senior Data Engineer to join our innovative Data team. You will join a collaborative team of data and AI engineers, scientists, developers, analysts, and architects. Together, we design and build modern machine learning and AI services that support analytics and improve products across the business.
Main Responsibilities
- Build and support data products within our modern data platform
- Design and deliver solutions with engineers, scientists and product teams
- Develop and optimise data pipelines across the analytics platform
- Integrate data from varied sources with strong quality standards
- Maintain orchestration, monitoring and performance of data components
- Improve engineering processes across the wider data community
- Promote high coding and data practice standards
- Experiment with emerging data, ML and AI technologies
- Partner with architects on data product designs
- Work collaboratively in multi-functional agile squads
- Support ML and GenAI infrastructure and workflows
Skills and Experience
- Passion for building scalable, resilient cloud data platforms
- Strong experience with Databricks or Snowflake on AWS
- Proven Python skills, including Spark and Airflow expertise
- Advanced SQL skills and endâtoâend data modelling experience
- Experience building batch and real-time data integrations
- Handsâon CICD skills with Git, Jenkins or similar
- Ability to ingest, cleanse and structure large, diverse datasets
- Knowledge of Terraform or similar IaC tools
- Experience with Docker and Kubernetes is beneficial
- Exposure to production Generative AI is an advantage
- Strong collaboration skills and a proactive attitude
Benefits
- Flexible working â Smart Working within the UK and workâday flexibility. Partâtime/Jobâshare options. Minimum 35 days holiday (including bank holidays) with option to buy/sell days.
- Health benefits â Dental insurance, Health Cash Plan, Health screening, Will Writing, Voluntary Critical Illness, Mental Health First Aiders, Wellâbeing activities â mindfulness.
- Wealth benefits â 50% off motor and home insurance, Annual Bonus Schemes, Annual Salary Reviews, Competitive Pension, Employee Savings, Employee Loans.
- Workâlife â Wellâbeing activities, mindfulness sessions, Sports and Social Club events.
- Family support â Maternity/pregnant parent/primary adopter entitlement of 16 weeks at full pay and paternity/nonâpregnant parent/coâadopter at 8 weeks' full pay.
- Benefits for them â Partner Life Assurance and Critical Illness cover.
- Tech deals â Deals on gadgets including wearables, tablets, laptops.
- Getting around â Car Salary Exchange, Cycle Scheme, Vehicle Breakdown Cover.
- Back to work â Return to work programme after maternity leave.
Equal Opportunity
We are an inclusive employer, encouraging anyone to apply. We are a signatory of Race at Work Charter, Women in Finance Charter, and member of iCAN, GAIN. We are a Disability Confident Leader and provide support and adjustments during recruitment.
Senior Data Engineer employer: Ageas
Contact Detail:
Ageas Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Senior Data Engineer
â¨Network Like a Pro
Get out there and connect with folks in the data engineering space! Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings or can put in a good word for you.
â¨Show Off Your Skills
Donât just tell us what you can do; show us! Create a portfolio of your projects, especially those involving Databricks, Snowflake, or any cool ML stuff you've worked on. This will give you an edge and make you stand out during interviews.
â¨Ace the Interview
Prepare for your interview by brushing up on your technical skills and being ready to discuss your experience with Python, SQL, and data pipelines. Practice common interview questions and think about how you can demonstrate your collaborative spirit and proactive attitude.
â¨Apply Through Our Website
We want to see your application! Make sure to apply through our website for the best chance at landing that Senior Data Engineer role. Itâs the easiest way for us to keep track of your application and get back to you quickly.
We think you need these skills to ace Senior Data Engineer
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your expertise in data engineering, especially with tools like Databricks or Snowflake, to show us youâre the right fit!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data engineering and how your background aligns with our innovative Data team. Be genuine and let your personality shine through!
Showcase Your Projects: If you've worked on relevant projects, donât hesitate to include them! We love seeing real examples of your work, especially if they involve building scalable data platforms or using machine learning technologies.
Apply Through Our Website: For the best chance of getting noticed, make sure to apply directly through our website. Itâs the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Ageas
â¨Know Your Tech Inside Out
Make sure you brush up on your skills with Databricks, Snowflake, and Python. Be ready to discuss your experience with data pipelines and how you've tackled challenges in previous projects. This is your chance to show off your technical prowess!
â¨Showcase Your Collaboration Skills
Since the role involves working with a diverse team, be prepared to share examples of how you've successfully collaborated with engineers, scientists, and product teams. Highlight any agile methodologies you've used and how they contributed to project success.
â¨Prepare for Scenario-Based Questions
Expect questions that ask how you'd handle specific situations, like optimising a data pipeline or integrating data from various sources. Think through your past experiences and be ready to explain your thought process and the outcomes.
â¨Ask Insightful Questions
At the end of the interview, donât forget to ask questions! Inquire about the team's current projects, the technologies theyâre excited about, or how they measure success in their data initiatives. This shows your genuine interest in the role and the company.