Your tasks

• You design and implement automated data quality checks across all data layers.
• You develop and maintain sidecar services or libraries to monitor and enforce data quality rules.
• You collaborate with Data Engineers to integrate data quality checks into Spark pipelines on Databricks.
• You define and maintain data quality metrics.
• You configure and manage alerting mechanisms for data quality incidents.
• You perform root cause analysis on data quality issues and work with the team to resolve them.
• You contribute to the creation of data quality dashboards and reports.
• You support the adoption of best practices around data validation and schema enforcement.
• You ensure the documentation of data entities, its data quality checks, and their rationale across datasets.

Your profile

• You have strong experience in Python or Scala, with a focus on backend or data-related systems.
• You are proficient in Spark and Databricks, and understand distributed data processing.
• You have hands-on experience implementing data quality frameworks or tools (e.g., Deequ, DQX, etc.).
• You are comfortable working with structured, semi-structured, and streaming data.
• You are have knowledge about writing automated tests and integrating them into CI/CD pipelines, as well as being familiar with terms like TDD or BDD.
• You understand the data quality challenges at each layer being proactive in identifying data issues.
• You are familiar with monitoring tools and alerting systems (e.g., Prometheus, Grafana, or alternatives).
• You can communicate effectively with both technical and non-technical stakeholders.
• You take ownership of your work and and have ideally already worked in agile teams.
• You have a passion and enthusiasm for new technologies and topics related to data.
• You have a good command of English.

We look forward to receiving your application.

Schwarz Dienstleistung KG · Xavier Coll Porqueres · Reference no. 46249 
Stiftsbergstraße 1 · 74172 Neckarsulm, Germany 
www.careers.schwarz