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Senior Software Engineer – Distributed Systems
DecentriqSenior Software/Data Engineer owning resilient Python and Spark pipelines for Decentriq’s privacy-preserving AdTech data-clean-room platform. Improving ML models, observability, and confidential-computing reliability.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and operating data pipelines using Python, pandas, and Spark, with a focus on data quality and validation. Proficient in collaborating with cross-functional teams to enhance machine learning models and ensure robust data processing in secure environments.
Highest-signal resume keywords
Expert-Level PythonPandas and PySpark/Scala SparkData Pipeline DevelopmentDatabricks and Spark on KubernetesConfidential Computing
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Pipeline DevelopmentMachine Learning Model ProductionizationData Quality ValidationDistributed Data ProcessingData Source ValidationPerformance TuningOrchestration Best PracticesAudience SegmentationLook-A-Like ModellingHomomorphic Encryption
Soft Skills
CollaborationProblem-SolvingCommunication
Tools & Technologies
DatabricksSparkKubernetesAirflowDagsterLLM-Based Code Assistants
Certifications & Qualifications
Bachelor's Degree in Computer ScienceMaster's Degree in Data EngineeringPhD in Related Field
Industry Keywords
AdTechConfidential ComputingSecure EnclavesBig Data PlatformsML Lifecycle
Tech Stack
Tools & technologiesAirflowCloudKubernetesPandasPySparkPythonRustScalaSpark
About the role
Key responsibilities & impact- Own, design, and operate all pandas- and Spark-based data pipelines from development through production and monitoring
- Improve and productionise ML models for AdTech use cases including look-a-like modelling, audience expansion, and campaign measurement
- Build robust data-source validation, exhaustive test coverage, and self-healing jobs for data inside confidential-computing enclaves
- Collaborate with data scientists, Rust backend engineers, and product teams to ship features end-to-end
- Leverage LLM-based code assistants, design generators, and test-automation tools; share workflows with the team
- Profile, benchmark, and tune Spark workloads
- Introduce best practices in orchestration and observability
- Keep the technology stack future-proof
Requirements
What you’ll need- Bachelor/Master/PhD in Computer Science, Data Engineering, or a related field
- 5+ years of professional experience
- Expert-level Python
- Solid hands-on experience with pandas, PySpark/Scala Spark, and distributed-data processing
- Proven track record building resilient, production-grade data pipelines with rigorous data-quality and validation checks
- Experience running workloads in Databricks, Spark on Kubernetes, or other cloud/on-prem big-data platforms
- Working knowledge of ML lifecycle and model serving (plus)
- Familiarity with audience segmentation or look-a-like modelling (plus)
- Exposure to confidential computing, secure enclaves, homomorphic encryption, or similar privacy-preserving technology (plus)
- Rust proficiency (plus)
- Data-platform skills including operating Spark clusters, job schedulers, or orchestration frameworks such as Airflow, Dagster, or custom schedulers (plus)
Benefits
Comp & perks- Competitive salary
- A lot of opportunities for self-development
- Ability to create, shape, and benefit from a young company
- Amazing and fun team distributed all over Europe
- Growing responsibilities as an individual contributor
- No need for a formal motivational letter