Data Engineer

Overview

Tech for People Unlocks the Future At Devoteam, we believe that technology, combined with strong human values, can actively drive change for the better. Discover how Tech for People is shaping the future, creating a positive impact on individuals and the world around us. With over 25 years of passion for technology and a presence in 18+ countries across EMEA and beyond, we are committed to leveraging innovation, expertise, and human-centric values to make a difference.

Devoteam Culture & Values: True innovation is born from a powerful culture, fused with meaningful values.

Culture: Fair and courageous. Everyone is treated fairly – this fuels bravery. We listen and are willing to be challenged, taking courageous decisions as a result. We help our employees to progress at every step and congratulate those who deserve it.

Ambition and results: Ambition is nurtured at every step – this drives results. We are ambitious entrepreneurs with a taste for performance, growth and celebrating success. Commitments are always kept as we seek to achieve profitable growth to create value and employment. We aim to bring as much value as possible to our clients, at every touchpoint.

Learning and innovating: Curiosity and learning are at our core – this stimulates innovation. We are curious. We learn and embrace innovation constantly to meet challenges and build partnerships of excellence.

Caring and sharing: A caring attitude is infused into our culture – this encourages sharing. We believe in the power of teams, and we promote support and collaboration. At Devoteam, we care about our teams and want to work in a positive, productive environment. We support the development of talent and careers.

Values:

• Respect
• Frankness
• Passion

A Data Engineer is expected to develop, monitor, and optimize data quality rules and processes to ensure reliable and accurate enterprise data. They identify and resolve data anomalies through profiling, cleansing, and validation workflows. The role ensures that business decisions are driven by complete, consistent, and high-integrity data across systems.

• Design, implement, and maintain data quality frameworks, rules, and processes to ensure the accuracy, completeness, and reliability of enterprise data.
• Collaborate with data governance, MDM, and data integration teams to enforce consistent data quality standards across systems.
• Conduct data profiling, anomaly detection, and validation to identify quality gaps and root causes.
• Develop automated data quality checks and workflows for continuous monitoring and remediation.
• Define and manage key data quality metrics (DQ KPIs) and build dashboards to visualize performance trends.
• Document data quality rules, issue logs, and remediation actions as part of the data governance framework.
• Work closely with business data stewards and domain owners to define data quality expectations and acceptance thresholds.
• Support audits, compliance reviews, and data management maturity assessments by providing DQ evidence and reports.
• Lead the design and deployment of scalable data quality solutions across multiple data domains and systems.
• Define enterprise data quality standards, policies, and rule frameworks aligned with governance strategy.
• Establish data quality scorecards, thresholds, and escalation workflows for high-impact issues.
• Conduct root cause analysis and lead remediation programs for chronic data issues.
• Mentor junior engineers and promote data quality best practices across teams.
• Participate in compliance with the local data management regulations (e.g. NDMO, NDI).
• Design, build, and maintain scalable, secure, and robust data pipelines for efficient data ingestion and transformation, with a strong focus on building quality checks into the infrastructure itself.
• Collaborate with cross-functional and leadership teams (Data Scientists, Analysts, and Business Leaders) to translate complex business requirements into technical data quality solutions.
• Research, evaluate, and recommend new data quality tools, technologies, and practices to enhance the reliability, security, and scalability of the data…