Senior Data Engineer

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

About Our Client

Our client is global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation. We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising. We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world.

We’re a Product & Engineering team that’s focussed on optimizing the impact that advertising has for audiences and the brands that we work with. We do this by optimising media buying, and employing dynamic creative, to deliver impactful and relevant messages. Getting these to the right audience, on the right medium, at moments and locations that matter, via channels and for a budget that is optimal for the brands we work with, is where we live.

This role will work primarily on our Creative Optimization product, an omnichannel dynamic content optimisation (DCO) platform, that enables brands to power ads (e.g. images, videos, copy) across a range of channels (display, social, online video, connected TV) with dynamic data (e.g. location, weather, events) in real-time, turning a single creative concept into thousands of unique stories. We utilise AI to optimize for the best performing content, helping advertisers to tell the right story at the right time, and audiences to see messages that matter.

Our culture is based on mutual trust, sharing, building, and learning together. We value simplicity, maintainability, automation, and metrics.

About This Role

Our team consists of 100+ engineers, designers, data, and product people, working in small inter-disciplinary teams closely with creative agencies, media agencies, and with our customers, to develop and scale our DCO platform, a leading digital advertising optimization suite that delivers amazing outcomes for brands and audiences.

As a Senior Data Engineer you will work with our Product and Engineering team, as well as other feature development teams, to build, deliver and operate our data platform. The role is a hands on data engineering role, analysing and sourcing data for our teams to use, building and maintaining pipelines and automations to wrangle, cleanse, secure, govern and provide that data to teams, scaling DS prototypes to operational ML solutions, building automations, owning tests, supporting junior engineers, and contributing to the wider team principles and practices, and the tools we use. The role has no line management responsibilities.

Our data platform is built with Python and Airflow, deployed using CI/CD, heavily exploits automations, and runs on GCP, k8s, Spark, Redis and more. Our efforts in data engineering support our adtech platform which supports hundreds of millions of ad buys annually. You’ll play a leading role in significantly scaling this further.

Responsibilities

• Work with product, product engineering, data engineering, and data science peers to build and support our AdTech platform.
• Build data-oriented solutions that are simple, scalable, reliable, secure, maintainable, and make a measurable impact.
• Provide our teams with the data they need to build, sell, and manage our platform, and scale DS prototypes into production solutions. Develop, deliver and maintain batch and real-time data pipelines, analysis services, workflows and orchestrations, and create and manage the platforms and data infrastructure that hold, secure, cleanse and validate, govern, and manage our data.
• Manage our data platform, incorporating services using Airflow, CloudSQL, BigQuery, Kafka, Dataproc, and Redis running on Kubernetes and GCP.
• Support our Data Science teams with access to data, performing code reviews, aiding model evaluation and testing, deploying models, and supporting their execution.
• Employ modern pragmatic engineering principles, practices, and tooling, including TDD/BDD/ATDD, XP, QA Engineering, Trunk Based Development, Continuous Delivery, automation, DevSecOps, and Site Reliability Engineering.
• Contribute to driving ongoing improvements to our engineering principles, practices, and tooling. Provide support & mentorship to junior engineers.
• Develop and maintain a contemporary understanding of AdTech developments, industry standards, partner and competitor platform developments, and commercial models, from an engineering perspective.
  
  

Requirements

• Experience architecting ML-based solutions in conjunction with DS teams, software engineering teams, and Product teams.
• Proven experience translating data science prototypes into production services with clear APIs, SLAs/SLOs, and acceptance criteria in high-volume, low-latency contexts (e.g., AdTech).
• Proven experience designing, building, and operating batch/streaming feature pipelines with schema control, validation, lineage, and offline/online parity using Python, Airflow/Composer, Kafka, and BigQuery; leveraging Spark, MySQL, and Redis as appropriate.
• Proven experience implementing reproducible ML training workflows (data prep, hyperparameter tuning, evaluation) with artifact and model versioning on public cloud (GCP strongly preferred).
• Proven experience packaging and deploying models as containers/services with staged promotion, canary/shadow/A/B rollouts, rollbacks, and environment parity via CI/CD.
• Proven experience running scalable inference (batch, microservice, streaming) that meets latency/error budgets, with autoscaling, observability, and SRE-style reliability practices.
• Proven experience establishing CI/CD for data and models with automated tests, data quality gates, model regression/drift detection, and API/data contract testing.
• Proven experience applying DevSecOps in ML systems: IAM, secrets management, network policies, vulnerability scanning, artifact signing, and policy-as-code on GCP.
• Proven experience collaborating with data science on feature design, labeling/annotation strategies, evaluation metrics, error analysis, and defining retraining triggers/schedules.
• Exposure to contributing to product strategy and KPI definition; planning experiments (A/B) and prioritizing ML features aligned to SaaS delivery and operational needs.
• Exposure to coaching and uplifting teams on data/ML testing, observability, CI/CD, trunk-based development/XP, and writing clear documentation (design docs, runbooks, model/data cards).
• Proven experience operating in ambiguous, fast-changing environments; iterating from prototype to production with safe rollouts, clear ownership, and continuous improvement.
• Strong English, excellent influencing and communication skills, and excellent documentation skills.
  
  

What you will love about working here?

• We care about all our employees and want them to feel as comfortable as possible. That's why we offer them health insurance from the first days, regardless of the probationary period.
• The gift from the company - Christmas holidays from 25 December to 31 December.
• Сooperation with Superhumans center and Veteran HUB. Capgemini Engineering has supported the launch of psychological rehabilitation department of Superhumans. Our team also donnated over UAH 500 000 prosthetics for three Ukrainian defenders. Currently, we support psychological counseling provided by the Veteran Hub, and we have implemented a internal policy making the company friendly to military and veterans with the assistance of the Hub.
  
  

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.