At a Glance
- Tasks: Design and optimise scalable data pipelines for customer decisioning.
- Company: Inclusive tech company fostering a positive culture and collaboration.
- Benefits: Comprehensive health plan, private healthcare, gym discounts, and wellness activities.
- Other info: Enjoy social events, volunteering days, and a flexible hybrid working model.
- Why this job: Lead impactful projects in data engineering and enhance your career in a supportive environment.
- Qualifications: Expertise in SQL, Python, Apache Spark, and experience with CI/CD practices.
The predicted salary is between 63000 - 77000 £ per year.
We are looking for an experienced Principal Data Engineer to take technical ownership of our customer decisioning pipeline architecture, end-to-end orchestration, and production readiness. In this role, you will lead the implementation of real-world targeting and eligibility rules, ensure bulletproof data quality, and oversee mission-critical downstream activation.
Responsibilities:
- Design, build, and optimize scalable data pipelines that run on reliable scheduled and event-triggered workflows.
- Implement and review complex business logic for customer eligibility, contact policies, suppression rules, and cooldown periods.
- Oversee downstream activation datasets, file manifests, delivery status tracking, and secure SFTP platform integrations.
- Drive engineering standards by reviewing pull requests and enforcing rigorous unit, integration, and regression testing across environments.
- Lead production cutovers, automated alerting, disaster recovery, data reconciliation, and technical incident response.
Requirements:
- You have deep expertise in building large-scale data engineering solutions using SQL, Python, Apache Spark, and Databricks.
- You bring proven experience designing resilient workflows with strict dependency management and idempotent processing.
- You are comfortable establishing robust CI/CD practices, conducting code reviews, and managing releases using Git and Azure DevOps.
- You have a track record of supporting production systems with automated data quality checks, reconciliation routines, and incident diagnosis.
Desirable:
- You ideally bring familiarity with CRM decisioning engines, marketing consent frameworks, or platform integrations like Comarch and Salesforce Marketing Cloud.
Conditions:
Our goal is to build an inclusive positive culture where everyone can feel comfortable being themselves, empowering people to create their own high standards and therefore more value. We work together to promote fairness while recognising, valuing and embracing differences – providing a transparent support structure and generous training budget to help our people develop skills to progress their career. Our region supports a hybrid model that can flex across a wide spectrum of working options determined by business, customer and individual needs. You'll benefit from a comprehensive health and wellness plan, private healthcare (clinical and mental wellbeing), discounted gym memberships, and in office yoga sessions and massages. We offer a fantastic benefits package including a competitive pension scheme and recognition schemes through bonus/reward initiatives. Colleagues are entitled to an annual volunteering day – so you can take time to support a cause close to your heart. We also love to stay social with trips to the zoo, quiz nights, sports events, theatre trips and much more.
Data engineer in customer decisioning employer: GlobalLogic
At GlobalLogic, we pride ourselves on being an exceptional employer, fostering a culture of inclusivity and empowerment that allows our employees to thrive. With a focus on professional growth, we offer opportunities for skill development in cutting-edge technologies within the dynamic field of digital engineering, particularly in financial services. Our collaborative environment encourages innovation and values diverse perspectives, making it a rewarding place to build a meaningful career.
StudySmarter Expert Advice🤫
We think this is how you could land Data engineer in customer decisioning
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like GlobalLogic.
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We think you need these skills to ace Data engineer in customer decisioning
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at GlobalLogic, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at GlobalLogic. 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 GlobalLogic
✨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!
✨Showcase Your Projects
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 GlobalLogic!
✨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.
