Data Quality Analyst

Datashift; Antwerpen; Sur place; EUR 52 000 - 76 000; Plein temps

Résumé du poste

Datashift is seeking a Data Quality Analyst to advise clients on building robust data quality frameworks and capabilities. You’ll help teams define standards, monitor data quality and embed best practices across business and technical domains.

The role emphasizes advisory work over hands-on tasks, with opportunities to lead improvements, design governance, and promote tool usage in a fast‑growing data environment.

Qualifications

• Bachelor’s or Master’s degree in a relevant field or equivalent experience.
• 2–5 years of consulting or service-oriented experience with at least 2 years in data analysis.
• Fluent in Dutch and/or French and English.

Responsabilités

• Develop and implement data quality standards and embed them in client operating rhythms.
• Advise clients on tool and technology improvements based on maturity and stack.
• Bridge business and technology on data quality needs, monitoring and remediation.
• Identify opportunities to improve workflows and drive automation with the toolkit.
• Promote data quality tooling and support adoption in key use cases.

Connaissances

Data quality principles

Leadership

Communication

Interpersonal skills

Entrepreneurial mindset

Formation

Bachelor’s or Master’s degree in a relevant field

Outils

SQL

Databricks

Snowflake

DBT

Python

Collibra DQ

Soda

Great Expectations

Informatica DQ

Description du poste

Introduction

For one of our fast growing practices, we are looking for a Data Quality Analyst. If the following questions spark your curiosity, this role might be exactly what you’re looking for:

• How do you define “good data quality” when working with unstructured data such as text and images?
• How do you approach the challenge of data quality for “AI” versus “AI for data quality”?
• What are the biggest blind spots organizations face when measuring data quality?
• How would you design a data quality framework for LLM-based applications?
• Case: A company wants to deploy an AI assistant or chatbot on top of poorly documented and inconsistent internal data—how would you approach this in your first 90 days?

Your Role

This is a primarily advisory position, focused on enabling rather than executing. While you’re comfortable stepping into hands‑on data challenges when needed, the role is not designed as a traditional staffing position embedded in day‑to‑day operational work.

Instead, you support clients in building the right frameworks, processes, and capabilities, empowering their teams to independently manage and improve their data quality landscape.

This is neither a pure data analysis nor data engineering role, and it goes beyond simply executing assigned tasks. You are expected to proactively identify opportunities and challenges, guide improvements, and provide clear direction in a fast‑evolving data environment.

In short: you create tangible, lasting impact.

Your Responsibilities

• Develop and implement data quality standards, communicate data (quality) principles fit for the specific client context and embed them in the client’s daily operating rhythm to improve trust in both business and technical data domains.
• Advice clients on tool and technology improvements in function of the client’s maturity, technology stack and needs.
• Support clients in their day‑to‑day activities by bridging the gap between business and technology on topics like data quality business needs, monitoring and remediation processes; train them on what good data quality looks like and inspire them with best practices and tooling knowledge.
• Identify opportunities to create more impact with the available tool stack, launch experiments to optimize workflows and collaborate with client teams to improve process automation accordingly.
• Help clients to internally promote its data quality tooling and refine its value proposition. Increase the adoption of the DQ tooling by supporting teams on its implementation in key use cases.

Your Qualifications

• Bachelor’s or master’s degree in a relevant field (engineering, IT, information management, etc.) or equivalent in experience.
• 2 to 5 years of experience in consulting or service‑oriented environments, and at least 2 years of experience in data analysis.
• Fluent in Dutch and/or French and English.

Skillset

• Capable to work with AI‑aided features in a responsible way.
• A strong grasp of data quality principles and why they matter to companies. You are able to identify risks and business impact of poor data quality.
• Understanding of how data is created, transformed and consumed across systems in companies. Understanding of data pipelines and modern data platforms (e.g. data warehouses, ETL/ELT processes).
• Data governance affinity and awareness of best practices. Specific cataloguing experience is a plus.
• Comfortable discussing with both business stakeholders and technical teams.
• Excellent leadership, communication (written and oral) and interpersonal skills.
• An entrepreneurial mindset to spot opportunities independently, since DQ teams are often small.

Technologies

• Proficiency in SQL
• Proficiency in Databricks or Snowflake or DBT
• Python *
• Experience with data quality tooling e.g., Collibra DQ*, Soda*, Great Expectations*, Informatica DQ* or experience with developing data quality checks in SQL*
• Nice to have. Eagerness to learn in these domains/skills is more important than current level

Your Growth Path

Datashift is a firm believer in growing through its people. We will guide and support you providing a multitude of opportunities to develop and grow in the direction you want. However we equally believe that it’s you who takes ownership of your growth. That’s why we give you the tools and the driving seat, it’s up to you to seize the opportunity.

One thing is for sure, surrounded by an entrepreneurial team, many opportunities will present themselves to deepen your expertise knowledge or broaden your responsibilities within a fast growing scale‑up.

Our Offer

• A highly entrepreneurial team where initiatives are highly valued and room is given to grow;
• A no‑nonsense working environment where you will have a direct impact and deliver meaningful results (whilst having a lot of fun);
• Excellent terms of employment;
• Joining a fast growing company means growing together with it: learn new skills, take a variety of responsibilities and opportunities that continuously present themselves
• Fringe benefits including continuous training that builds and extends professional, technical and management skills in all areas;

Interested?

Don't hesitate to apply via the link below!