Adikteev

Data engineer for machine learning

In short

Senior Data Engineer role owning the ML Platform at an AdTech company, architecting and scaling data infrastructure for real-time and batch ML workflows that power predictive advertising systems. Requires proven Data Engineering experience with Apache Spark and Airflow, a focus on MLOps, feature engineering, and fluent English; candidates must be legally authorized to work in the EU. Fully remote with a 4.5-day work week and OTE salary of 80,000–90,000€.

About the Company
Adikteev is an AdTech company that helps mobile app publishers grow their revenue through targeted advertising. We deliver personalized ads that drive users to install an app or re-engage with one they've stopped using. We are looking for a Senior Data Engineer to take ownership of our ML Platform. You will help design, deploy, and evolve predictive models that power Adikteev's core adtech systems and you will be the architect of the infrastructure that enables our ML models to scale, perform, and deliver value at high velocity.
Responsibilities
•Architect, scale, and maintain our data infrastructure, ensuring it meets the rigorous demands of real-time and batch ML workflows.
•Make sure data is always available: oversee processing, storage, aggregation, and API development.
•Streamline our data processes by integrating efficient testing, monitoring, alerting, and error recovery.
•Design and implement our feature store to centralize feature discovery, storage, and serving and build robust feature engineering pipelines.
•Build and optimize highly scalable pipelines using Apache Airflow and Apache Spark, focusing on high reliability and cost-efficiency.
•Contribute to innovation efforts, by exploring promising ideas from recent academic work and turning them into production-grade solutions.
•Leverage AI coding tools (Copilot, Cursor, etc.) to accelerate development cycles and stay at the forefront of engineering productivity.
•Drive best practices for data quality, CI/CD for data, and technical documentation.
•Mentor peers and identify infrastructure bottlenecks before they impact the business.
Requirements
•Proven track record as a Data Engineer, ideally with a focus on MLOps and production-related challenges (latency, throughput, server cost optimization...).
•Hands-on expertise with Apache Spark (tuning, scaling), Airflow (complex DAG orchestration).
•Solid understanding of how to transform raw data into high-quality features for machine learning.
•A "Product Owner" mentality for data, you don't just ship code; you own the reliability and scalability of the systems you build.
•Fluent in English and the ability to articulate complex architectural choices to both technical and non-technical stakeholders.
•Applicants are required to maintain residency and be legally authorized to work in the European Union in order to be considered for this position.
Nice to Have
•Kafka streaming and Kubernetes are a plus.
•Our stack runs on AWS so a good knowledge of this platform is also a plus.
•Hands-on experience with Python and Java/Scala is a plus.
•Experience with tabular data for classification problems and deep learning is a plus.
•Experience building or maintaining feature stores.
•Notions of French can be a plus.
Conditions
•Competitive Salary between 80,000 and 90,000€ OTE. The salary range shown reflects total On-Target Earnings (OTE), including base salary and a performance-based Quarterly bonus with transparent KPIs.
•4 1/2 days work week (Fridays afternoon off).
•Longevity bonus every 2 years.
•Healthcare plan with excellent coverage.
•Lunch Vouchers.
•Mental Health support.
•Flexible remote working policy.
•Regular team-life event / activity.
•Inclusive parental leave Policy.

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