Hybrid Data Quality Engineer – SQL/Snowflake/Python (Sales)

HumanIT Digital Consulting; Lisboa; Híbrido; EUR 22 000 - 30 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

15th month salary

Health insurance

Birthday off

Mobility program

Work-life balance

Resumo da oferta

HumanIT Digital Consulting in Lisbon is seeking a Data Quality Engineer for Sales & Finance Data Products, focusing on data quality across group-wide data assets. Hybrid work with 1–2 office days per week, with potential changes to visits per month.

Strong SQL, Snowflake and Python skills are required. The role emphasizes translating business rules into automated quality checks, dashboards and SLA monitoring, collaborating with Sales and Finance stakeholders to ensure reliable data for reporting

Qualificações

• Degree in Computer Science, Business Informatics, Data Engineering, Mathematics, Finance, Industrial Engineering or a comparable field
• Several years of practical experience in data quality, data engineering, analytics engineering or a comparable data-focused role
• Strong SQL skills and hands-on experience with data profiling, validation, reconciliation, root-cause analysis and automated testing
• Experience with modern cloud data platforms and data pipelines, ideally Snowflake, including data modelling and transformation frameworks
• Knowledge of data quality dimensions, controls, monitoring, metadata, lineage and data governance principles
• Understanding of Sales and Finance processes and data: customer and lead management, revenue, pricing, costs, profitability, planning and financial reporting
• Scripting or programming experience, preferably Python, plus version control and CI/CD practices
• Ability to turn complex business definitions into clear, testable rules and to explain quality issues in business terms
• Practical experience using AI tools for data profiling, quality analysis, anomaly detection, root-cause analysis, documentation and data engineering delivery
• Strong analytical skills, attention to detail, and a structured, proactive and independent working style
• Confidence working across business functions, countries and technical teams, and driving issues through to a lasting fix
• Languages: Very good English (B2 Upper Intermediate minimum)

Responsabilidades

• Design, implement and continuously improve group-wide data quality controls covering completeness, accuracy, consistency, validity, timeliness and uniqueness
• Translate business rules into measurable data quality rules, automated tests, monitoring and alerting
• Build and maintain data quality dashboards, scorecards, issue logs and service-level indicators for reporting across countries and business functions
• Analyse anomalies and recurring issues, run root-cause analysis and coordinate lasting fixes with data owners, source-system teams and data product teams
• Embed automated quality checks into data pipelines and development processes, so defects are caught before they reach reports, analytics or AI use cases
• Define critical data elements, validation standards, quality thresholds, ownership and escalation paths in line with the group data governance framework
• Work with Sales and Finance stakeholders to improve the reliability of customer, lead, revenue, volume, pricing, cost, profitability and reporting data
• Contribute to shared engineering standards, documentation and reusable data quality components across the decentralised group data platform

Conhecimentos

SQL

Python

Data profiling

Root-cause analysis

CI/CD

Data governance

Analytical thinking

Cross-functional collaboration

English (B2)

Formação académica

Degree in Computer Science or related field

Ferramentas

Snowflake

Python tooling

CI/CD tooling

Descrição da oferta de emprego

HumanIT Digital Consulting in Lisbon is seeking a Data Quality Engineer for Sales & Finance Data Products, focusing on data quality across group-wide data assets. Hybrid work with 1–2 office days per week, with potential changes to visits per month.

Strong SQL, Snowflake and Python skills are required. The role emphasizes translating business rules into automated quality checks, dashboards and SLA monitoring, collaborating with Sales and Finance stakeholders to ensure reliable data for reporting