Data Engineer, AI-Native Ad Tech Pipelines & Insights

Data Engineer, AI-Native Ad Tech Pipelines & Insights

Full-Time 63000 - 77000 £ / year (est.) No working from home possible
Adorphic Tech

At a Glance

  • Tasks: Own and optimise data pipelines for billions of bid events, shaping datasets for insights.
  • Company: Join Adorphic Tech, a leader in AI-native ad technology.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on innovation and data quality.
  • Why this job: Make an impact in the fast-paced world of ad tech with cutting-edge data solutions.
  • Qualifications: 3-5 years in data engineering, strong SQL skills, and experience with Spark or Flink.

The predicted salary is between 63000 - 77000 £ per year.

Adorphic Tech is seeking a data engineer to own batch and streaming pipelines handling billions of bid events, shaping datasets for reporting and partner insights.

You will partner with the ML team to deliver features and training data, while prioritizing data quality, lineage, and cost-aware infrastructure.

Three to five years in data engineering with large event data, strong SQL, and experience with Spark or Flink will be essential.

Ad-tech/bidstream experience is a plus in this role.

#J-18808-Ljbffr

Data Engineer, AI-Native Ad Tech Pipelines & Insights employer: Adorphic Tech

At Adorphic Tech, we pride ourselves on being an excellent employer by fostering a collaborative and innovative work culture that empowers our data engineers to thrive. Located in a vibrant tech hub, we offer competitive benefits, continuous learning opportunities, and the chance to work with cutting-edge technologies in AI-native ad tech. Join us to be part of a team that values your contributions and supports your professional growth in a dynamic environment.

Adorphic Tech

Contact Details:

Adorphic Tech Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Engineer, AI-Native Ad Tech Pipelines & Insights

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Adorphic Tech!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer, AI-Native Ad Tech Pipelines & Insights at Adorphic Tech.

Leverage Professional Networks

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 Adorphic Tech.

Apply Directly through Our Website

When you find a suitable opening like Data Engineer, AI-Native Ad Tech Pipelines & Insights at Adorphic Tech, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Data Engineer, AI-Native Ad Tech Pipelines & Insights

SQL
Python
Problem-Solving Skills
Data Pipeline Development
Data Engineering
Communication Skills
API Integration

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 Adorphic Tech, 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 Adorphic Tech. 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 Adorphic Tech

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 Adorphic Tech!

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.