Data Quality Developer

ALDI aldi-hofer.com Open · verified Oct 24, 2026

Pécs Mid-level Data Architecture & Governance

At a glance

Mid-level Data Architecture & Governance role at ALDI. Pécs.

Pay not stated Data Architecture & Governance salary

RoleData Architecture & Governance

SeniorityMid-level

LocationPécs

PostedSep 26, 2026 · 4w ago

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Build checks for master, transactional, in-transit, reconciliation, and reporting data
Create table monitors for delays, broken pipelines, freshness, volume shifts, and schema changes
Track KPI anomalies and cross-system differences, checking results against agreed tolerances
Write row-level business validations and flag costly queries that risk timeouts or data incidents
Add monitoring to data product workflows, investigate incidents with engineering and analytics, and document alerts

What you bring

You have practical experience creating data checks and running monitoring for structured data
You bring strong SQL and Python skills, plus working knowledge of data management, quality, and architecture
You understand how to turn data quality dimensions into measurable checks
You can communicate and collaborate with data engineering, data product, and analytics teams, and have upper-intermediate English or better

Who this fits

This full-time role is based at the stated Pécs address. It suits someone who can work across data engineering and analytics teams and handle monitoring from setup through ongoing operations.

From the employer

MUNKAVÉGZÉS HELYE
7622 Pécs, Bajcsy-Zsilinszky utca 33.

TEVÉKENYSÉGI TERÜLET
IT

MUNKAVÉGZÉS KEZDETE
Megegyezés szerint

FOGLALKOZTATÁS MÉRTÉKE
Teljes munkaidő

megállapodás szerint

My responsibilities:

Implement data quality checks across multiple data domains, including master data, transactional data, data in transit, reconciliation, and analytical/reporting data
Build and maintain Table Monitors to detect pipeline delays/breakages and data health issues per table/view, including: freshness, volume expectations, and schema changes
Build and maintain Metric Monitors to identify anomalies in key statistical/business KPIs and to run comparisons/reconciliation across systems (e.g., different instances or data warehouses) while validating agreed tolerances
Build and maintain Validation Monitors to identify bad individual rows and enforce business logic (e.g., custom SQL validations for complex master data logic; row-level business rules)
Build and maintain Query Performance Monitors to detect inefficient/problematic queries that increase compute costs or risk timeouts and downstream data quality incidents
Integrate data quality monitoring into the data pipeline / data product lifecycle (setup, deployment, and ongoing operational maintenance)
Collaborate with data engineers and analytics teams to investigate data quality incidents, perform root-cause analysis, and implement preventive fixes
Document implemented checks/monitors, including intended meaning, owners, and guidance on how to interpret alerts

The knowledge I own:

Good knowledge of data management, data quality, and data architecture
Practical experience implementing data quality rules/checks and operating quality monitoring solutions for structured data
Strong skills in SQL and Python
Understanding of data quality dimensions (completeness, correctness/accuracy, consistency, uniqueness, validity, timeliness) and how to translate them into measurable checks
Familiarity with data-in-transit monitoring and reconciliation patterns across systems
Strong collaboration and communication skills to work with multiple stakeholders (data engineering, data product, analytics/reporting)
Background in data engineering environments (advantage): data lake/warehouse, pipeline orchestration, and CI/CD for data/pipeline changes
Experience with data quality tooling/platforms (advantage), e.g., Syniti or Monte Carlo
Experience with SAP and/or integration architecture (advantage)
Good command of English (upper-intermediate level or higher)
Ability to work in an agile environment