An organization is looking for a Data Engineer to take over, operate, and evolve its data environment. This role is central to ensuring the reliability, structuring, and exploitation of company data. The assignment covers data engineering, data quality, governance, reporting, and analytics, with a strong operational and transversal dimension. The objective is to provide reliable, structured, and exploitable data, enabling teams to manage their activities, improve processes, and make decisions based on quality data.
What you do
Data quality & governance:
- Analyze and guarantee the quality, reliability, and consistency of data
- Maintain data contracts and automated quality controls
- Implement monitoring and alerting mechanisms
- Ensure compliance with GDPR requirements and good governance practices
Data engineering & architecture:
- Design, develop, and maintain data transformation pipelines
- Integrate new data sources into the datalake
- Ensure daily run and monitoring of production pipelines
- Manage schema evolutions and DDL changes
- Implement entity matching and resolution techniques
- Contribute to the evolution and reliability of the data architecture
- Manage platform costs (FinOps): attribution, monitoring, optimization
Reporting, analytics & visualization:
- Administer and evolve the data visualization platform (Metabase), including permissions and secure embedding
- Design dashboards, metrics, and reports for internal teams and external partners
- Translate business needs into concrete data solutions
- Collaborate with different teams to transform data into actionable indicators and analyses
Data analytics, AI & continuous improvement:
- Maintain and retrain existing forecasting models
- Explore and integrate generative AI, automation, and Machine Learning solutions into Data processes
- Contribute to the development of a fraud detection methodology
- Identify opportunities for automation and optimization of Data processes
- Participate in transversal Data projects and continuous improvement
Profile
An autonomous, experienced profile is sought, capable of intervening across the entire data chain, from source integration to data availability and exploitation. The assignment starts with taking over an existing scope; the ability to read, understand, and appropriate a densely documented platform is crucial.
The data platform is in production on Databricks, it ingests data from application databases, Cognito, and S3, transforms it according to a medallion architecture, and feeds internal reports and dashboards for clients. The platform has been built over the last two years and is currently documented. The proposed mission involves taking responsibility for it and continuing ongoing projects.
What they ask
- Minimum 5 years of experience in a data environment (Data Engineer, Data Analyst, Data Scientist, or similar function)
- Strong proficiency in Python and PySpark
- Confirmed experience with Databricks in production: Unity Catalog, Delta Lake, Jobs, and deployment via Asset Bundles (or equivalent infrastructure-as-code)
- Comfortable with Git and CI/CD pipelines
- Good command of SQL and relational databases (MySQL)
- Experience in data design, transformation
- Experience in designing and maintaining data pipelines
- Good understanding of Data Quality and Data Governance challenges
- Sensitivity to and control of cloud platform costs
- Knowledge of matching, deduplication, fuzzy matching, and entity resolution techniques
Preferences.
- Experience with the AWS ecosystem (S3, Lambda, SQS) – a plus for Elasticsearch
- Experience in administering a BI tool (Metabase, Superset, or equivalent)
- Experience in Machine Learning, particularly applied to fraud detection
- Experience in integrating generative AI solutions and automation into Data processes
Qualities.
- Strong autonomy and ability to manage an end-to-end data scope
- Ability to work as a Data referent with various stakeholders
- Analytical and pragmatic mindset
- Ability to understand business challenges and translate them into technical solutions
- Proactivity and ability to propose improvements
- Comfort in a transversal environment and in collaboration with different departments
How to apply
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