Data Quality Analyst

Talent Quanta

TalentQuanta combines the agility of a boutique consultancy with the insight of a data-driven recruitment partner. Our approach blends deep sector knowledge with advanced research and network intelligence to deliver precise, high-impact results.

THE MISSION

On behalf of a confidential public sector institution in Luxembourg, we are looking for an experienced Data Quality Analyst to join a small, focused team building a structured and sustainable data quality management.

The institution manages several critical databases (case management, individuals, decisions, procedures, reference data, users, statistics) and wants to move from ad-hoc, partial data quality checks to a centralised, governed and automated control framework, built on Great Expectations and Apache Airflow.

The Data Quality Analyst leads the functional side of this mission: analyzing the databases, profiling the data, and defining a documented, versioned referential of technical and business quality rules — working closely with internal teams, who validate every rule before it is implemented.

The Data Quality Analyst will work in close collaboration with a Data Quality Developer, who implements the rules the Analyst defines and validates into Great Expectations and automates their execution with Apache Airflow.

Responsibilities

The Data Quality Analyst will be responsible for data analysis, identifying quality issues, and defining

control rules.

In This Capacity, They Will Notably Be Required To

• analyze the anonymized databases, data models, the relationships between tables, and the data flows;
• carry out data profiling in order to identify anomalies, inconsistencies, duplicates, missing values, and
  
  

other quality issues;

• identify critical data and assess the risks related to their quality;
• organize and facilitate work workshops in order to understand the functional needs and business rules;
• define the data quality rules covering technical and business controls;
• identify the quality dimensions concerned (completeness, validity, uniqueness, coherence, accuracy,
  
  

referential integrity, temporal coherence, etc.);

• define the expected conformity thresholds for each quality rule;
• prioritize the quality rules according to their criticality and business stakes;
• document each rule in a centralized quality rules referential;
• maintain this referential throughout the mission;
• regularly present the defined rules to the team and management in order to obtain their functional validation before any implementation.
  
  

Each quality rule must notably be documented by means of the following information: unique identifier; rule

name; functional description; business domain concerned; application concerned; database, table(s), and

column(s) concerned; rule type (technical or business); quality dimension concerned; criticality level;

priority; expected conformity threshold; business owner (Data Owner); execution frequency; reference

SQL query, where applicable; corresponding Great Expectations implementation; validation status;

version number; modification history.

The provider may propose any additional metadata deemed useful to improve the management and

governance of the quality rules.

MUST HAVE

• Significant experience in similar missions involving data governance, data quality, or the
  
  

implementation of data quality control solutions (supporting references required).

• French or Luxembourgish -fluent CEFR B2 or above
• English — fluent, CEFR B2 or above
• Hands-on data profiling experience (detecting anomalies, duplicates, missing values, inconsistencies)
• Strong SQL, with experience analyzing data models, table relationships, and data flows in relational
  
  

databases

• Experience defining and documenting quality rules across dimensions such as completeness, validity,
  
  

uniqueness, referential integrity, temporal coherence, and accuracy

• Comfortable running/facilitating workshops with both business and technical stakeholders, and
  
  

translating functional needs into concrete control rules

• Experience building and maintaining a structured, versioned rules/metadata referential
  
  

GOOD TO HAVE

• Familiarity with data governance frameworks (e.g. DAMA-DMBOK)
• Experience with Master Data Management or data catalogue initiatives
• Public-sector experience, or experience handling sensitive/confidential data
• Exposure to decisional architectures (Data Warehouse, Data Lake, ETL/ELT)
  
  

MISSION RHYTHM

Minimum 3 days/week, partly remote/ on-site presence required for workshops and team meetings.

Apply Now

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