At a Glance
- Tasks: Design and build scalable data pipelines using AWS and develop strategies for data standardisation.
- Company: Join Barclays, a leading financial services provider, in a dynamic Cross Markets team.
- Benefits: Competitive salary, career development opportunities, and a collaborative work environment.
- Other info: Work in London with a focus on continuous improvement and leadership development.
- Why this job: Make an impact by leveraging data analytics to drive innovation and strategic decision-making.
- Qualifications: Experience in data engineering, AWS technologies, and financial services preferred.
The predicted salary is between 60000 - 80000 £ per year.
hackajob is collaborating with Barclays to connect them with exceptional professionals for this role. We are seeking an experienced Data Strategy Engineer to join our Cross Markets team where you will industrialise data standardisation across all cross‑market apps, develop consolidated strategies, and translate platform capability into measurable outcomes.
To be successful in this role you will:
- Design and build scalable data pipelines using AWS services like AWS Glue, Databricks, DIH and S3.
- Develop efficient ETL processes for data extraction, transformation, and loading into data warehouses and lakes.
- Create and manage applications using Python, SQL, Databricks, and various AWS technologies.
Previous financial services experience, ideally within investment banking, is required. Other skills that would be useful in this role include:
- .NET
- MS SQL
- Tableau
- Stakeholder Engagement experience
You may be assessed on key critical skills relevant for success in the role, such as risk and controls, communication skills and interaction with a diverse range of stakeholders, as well as job‑specific technical skills. This role is based out of our London office.
Purpose of the role:
To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision‑making, improve operational efficiency, and drive innovation across the organisation.
Accountabilities:
- Identification, collection, extraction of data from various sources, including internal and external sources.
- Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
- Development and maintenance of efficient data pipelines for automated data acquisition and processing.
- Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
- Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
- Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.
Vice President Expectations:
- To contribute or set strategy, drive requirements and make recommendations for change.
- Plan resources, budgets, and policies; manage and maintain policies/processes; deliver continuous improvements and escape breaches of policies/procedures.
- If managing a team, define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes.
- Lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements.
- If the position has leadership responsibilities, demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
Data Strategy Engineer employer: hackajob
Barclays is an exceptional employer that fosters a dynamic and inclusive work culture, particularly within its London office. As a Data Strategy Engineer, you will benefit from opportunities for professional growth and development, working alongside talented colleagues in a collaborative environment that values innovation and strategic thinking. With a commitment to employee well-being and a focus on driving excellence, Barclays empowers its team members to thrive while making meaningful contributions to the financial services industry.
StudySmarter Expert Advice🤫
We think this is how you could land Data Strategy Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for those interviews! Research Barclays and their data strategy initiatives. Show them you’re not just another candidate, but someone who’s genuinely interested in their mission.
✨Tip Number 3
Practice your technical skills! Brush up on AWS services, Python, and SQL. You might get asked to solve a problem on the spot, so being sharp will give you an edge.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Data Strategy Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Strategy Engineer role. Highlight your experience with AWS services, Python, and SQL, and don’t forget to mention any financial services background you have. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data strategy and how your previous experiences make you a perfect fit for our Cross Markets team. Keep it engaging and personal – we love to see your personality come through!
Showcase Relevant Projects:If you've worked on projects that involved data pipelines, ETL processes, or machine learning, make sure to showcase them in your application. We’re keen to see real examples of your work and how you’ve used data to drive results.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details you need about the role and our company culture there!
How to prepare for a job interview at hackajob
✨Know Your Data Tools
Make sure you’re well-versed in AWS services like Glue, Databricks, and S3. Brush up on your Python and SQL skills too, as these will be crucial for the role. Be ready to discuss specific projects where you've used these technologies to solve real-world problems.
✨Showcase Your Financial Services Experience
If you have previous experience in financial services or investment banking, highlight it! Prepare examples of how you've applied data strategies in those environments. This will demonstrate your understanding of the industry and its unique challenges.
✨Prepare for Stakeholder Engagement Questions
Expect questions about how you’ve engaged with stakeholders in the past. Think of examples where you’ve successfully communicated complex data insights to non-technical audiences. This shows your ability to align with business needs and drive value from data.
✨Demonstrate Leadership Behaviours
Whether you're applying for a leadership role or not, be prepared to discuss how you embody the LEAD behaviours: Listen, Energise, Align, and Develop. Share instances where you've inspired others or contributed to team success, as this aligns with the company’s values.
