Data Quality Developer

Stack

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 (freshness, volume expectations, schema changes)
• ▹Build and maintain Metric Monitors to identify anomalies in key statistical/business KPIs and to run cross-system comparisons and reconciliation while validating agreed tolerances
• ▹Build and maintain Validation Monitors to identify bad individual rows and enforce business logic (custom SQL validations, row-level business rules)
• ▹Build and maintain Query Performance Monitors to detect inefficient queries that increase compute costs or risk timeouts
• ▹Integrate data quality monitoring into the data pipeline / data product lifecycle (setup, deployment, ongoing operations)
• ▹Collaborate with data engineers and analytics teams to investigate data quality incidents, perform root-cause analysis and implement preventive fixes
• ▹Document the implemented checks and monitors, including intended meaning, owners and guidance on interpreting alerts

Requirements

• ▹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 SQL and Python skills
• ▹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)
• ▹Good command of English (upper-intermediate level or higher)
• ▹Ability to work in an agile environment

Nice to have

• ▹Background in data engineering environments: data lake/warehouse, pipeline orchestration, CI/CD for data/pipeline changes
• ▹Experience with data quality tooling/platforms, e.g. Syniti or Monte Carlo
• ▹Experience with SAP and/or integration architecture

Soft skills

What we offer

• ▹A constantly growing organization and increasing opportunities
• ▹Secure, long-term job opportunity
• ▹Varied and engaging job responsibilities
• ▹Outstanding salary
• ▹Flexible work arrangements
• ▹Home office possibility