Data Media Optimization

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.YOUR PROJECTOur 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 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 focussed on 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.YOUR TASKSWork 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. YOUR PROFILEExperience 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). What You’ll Love About Working HereWell-being culture: medical care with Medicover, private life insurance, and Sports card. But we went one step further by creating our own Capgemini Helpline offering therapeutical support if needed and the educational podcast 'Let's talk about wellbeing' which you can listen to on Spotify.Access to over 70 training tracks with certification opportunities (e.g., GenAI, Excel, Business Analysis, Project Management) on our NEXT platform. Dive into a world of knowledge with free access to Education First languages platform, Pluralsight, TED Talks, Coursera and Udemy Business materials and trainings.Continuous feedback and ongoing performance discussions thanks to our performance management tool GetSuccess supported by a transparent performance management policy.Enjoy hybrid working model that fits your life - after completing onboarding, connect work from a modern office with ergonomic work from home, thanks to home office package (including laptop, monitor, and chair). Ask your recruiter about the details.GET TO KNOW USCapgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. We evaluate individuals based on qualifications and performance, not personal characteristics, striving to create a workplace where everyone can succeed and feel valued.Do you want to get to know us better? Check our Instagram — @capgeminipl or visit our Facebook profile — Capgemini Polska. You can also find us on YouTube.About CapgeminiCapgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 360,000 team members globally in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms.Apply now!