Data Quality Engineer – Sales & Finance - Hybrid Lisbon (1-2 days/week office)

HumanIT Digital Consulting

Lisboa

Hybrid

EUR 22,000 - 30,000

Full time

3 days ago

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Benefits offered by this job

15th month salary

Health insurance

Birthday off

Mobility program

Work-life balance

Job summary

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

Qualifications

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)

Responsibilities

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

Skills

SQL

Python

Data profiling

Root-cause analysis

CI/CD

Data governance

Analytical thinking

Cross-functional collaboration

English (B2)

Education

Degree in Computer Science or related field

Tools

Snowflake

Python tooling

CI/CD tooling

Job description

Data Quality Engineer – Sales & Finance (SQL/Snowflake/Python) - Hybrid Lisbon (1-2 days/week office)

ABOUT THE OPPORTUNITY

Join the BI Platform Team of one of Europe's leading parcel and logistics groups. It offers B2B, B2C and C2C delivery, logistics and express services, connecting local businesses and global enterprises across dozens of countries. The team builds the foundation for data-driven decisions across the group. Its modern, decentralised data architecture covers everything from raw data and self-service to machine learning and visual analytics. In this role you'll own data quality for group-wide Sales & Finance Data Products. The data you protect is what business and financial decisions are made on.

PROJECT & CONTEXT

The goal of the Sales & Finance Data Products is to make sales and financial performance measurable and transparent across the full business lifecycle. That runs from leads and opportunities to new customers, parcel volumes, pricing, revenue, costs, profitability and financial reporting. You will:

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

Work model:

Hybrid. The office is in Venda do Pinheiro (Mafra/Malveira area, Greater Lisbon). You'll start with 1–2 office days per week, which may later drop to 1–2 visits per month. Full remote is not available.

WHAT WE'RE LOOKING FOR (Required)

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)