Staff Data Platform Engineer

Staff Data Platform Engineer

Full-Time 66150 - 80850 £ / year (est.) Home office (partial)
K

At a Glance

  • Tasks: Build a cutting-edge data platform that empowers clients to manage their own campaigns.
  • Company: Join Kargo, a leader in innovative advertising technology with a vibrant culture.
  • Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
  • Other info: Join a diverse team committed to innovation and excellence in the ad tech space.
  • Why this job: Be a founding engineer shaping the future of data management in advertising.
  • Qualifications: Experience in building APIs, SDKs, and production services in Python is essential.

The predicted salary is between 66150 - 80850 £ per year.

Kargo creates powerful moments of connection between brands and consumers to build businesses. Every day, our 600+ employees work to radically raise the bar on what agentic AI, CTV, eCommerce, social, and mobile can do to deliver unique ad experiences across the world's most premium platforms. Taking a creative science approach to all we do, we continuously innovate solutions that outperform industry benchmarks and client expectations. Now 20+ years strong, Kargo has offices in NYC, Chicago, LA, Dallas, Sydney, Auckland, London and Waterford, Ireland.

Kargo is building toward a unified platform where advertisers run campaigns across CTV, web, mobile apps, and social entirely self-serve. This is the first time that capability goes directly into clients' hands. Clients will pull their own reports, debug their own setups, and ask why a campaign isn't pacing, so the data behind them must be quick to extend, stable enough to trust, and structured for automated triage. Our pipelines already run at that scale, but each demand is met one team at a time: reporting is bespoke, stability rests on each team's own practice and monitors, and triage depends on whoever knows the pipeline. We're standing up a Data Platform team to solve these problems once for the whole company, and you'll be its founding engineer.

Working directly with the Sr. Director of Data Engineering, you'll shape the standards and build the software that enables and enforces them, open the platform up to contributors across Kargo, and grow the team as its scope expands. You'll own it as a long-term product: modular tools and paved roads that let any team publish data and have it arrive discoverable, reliable, and observable enough to triage without tribal knowledge.

The Daily To-Do:

  • Build the data control plane. One place to see and govern what data products exist: schemas, lineage, ownership, freshness commitments, quality, access. Built for people browsing and agents querying.
  • Build the paved road for standing up a data product. Libraries, SDKs, templates, and data-specific CI/CD on Kargo's engineering platform, plus a supported near-real-time pattern. Following the standard should be easier than bypassing it.
  • Build the enforcement layer for the data standards. Schema registry, the contract validator and the CI step that runs it, automated certification. Make every data product observable by default. Freshness, volume, schema conformance, and quality instrumented by the paved road rather than hand-built per team, emitting into Kargo's existing monitoring with the ownership and lineage metadata that makes AI-assisted triage possible.
  • Set the platform's technical direction. Architecture, roadmap, and build-versus-buy calls, informed by what the teams who produce and consume data actually need. Run the design reviews where they weigh in, and keep the platform modular enough that they contribute capabilities back.

Qualifications:

  • You've built loosely coupled production services, APIs and SDKs in Python that multiple teams depend on.
  • You've built metadata-driven platforms that integrate with catalogs and check lineage, contracts and quality automatically.
  • You've built observability other teams depend on, and can tell a signal from noise.
  • You get tools adopted by teams that don't report to you through architecture reviews, mentorship, and clear communication.
  • Strong AWS, Terraform and Kubernetes experience.

Strongly Preferred:

  • Experience moving from batch to streaming; understanding of cost tradeoffs.
  • Spark and Iceberg at significant scale, and Snowflake in production.
  • Ad tech, or another domain with high-volume event data and multiple consumers.
  • Experience building tooling and data structures that AI agents operate against.

Nice to have:

  • Experience standing up a platform team's first generation of capabilities.
  • Data catalog, semantic layer, or governance tooling.

Kargo is an Equal Opportunity Employer. We are committed to building an inclusive and diverse workplace where all employees and applicants are treated with respect and dignity. We do not discriminate on the basis of race, color, ethnic origin, religion or belief, sex, sexual orientation, gender identity or expression, age, disability, marital or family status, national origin, veteran status, or any other characteristic protected by applicable local, state, or federal law. All qualified applicants will receive consideration for employment.

Staff Data Platform Engineer employer: kargo

Kargo is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As the founding Data Platform Engineer, you will have the unique opportunity to shape the future of our data platform while enjoying comprehensive benefits and ample opportunities for professional growth in a vibrant tech environment. Located in a thriving area, Kargo provides a supportive atmosphere where your contributions directly impact the success of our advertising solutions.

K

Contact Details:

kargo Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Data Platform Engineer

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 kargo!

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 Staff Data Platform Engineer at kargo.

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 kargo.

Apply Directly through Our Website

When you find a suitable opening like Staff Data Platform Engineer at kargo, 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 Staff Data Platform Engineer

Python
APIs
SDKs
Metadata-Driven Platforms
Data Lineage
Data Quality Assurance
Observability

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 kargo, 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 kargo. 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 kargo

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 kargo!

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.