Data Analytics Manager

What you will be doing: Key responsibilities

As a Data Analytics Manager, your role will encompass:

Deliver the highest standards of quality on Data marketing projects

• Pilot multidisciplinary teams (consultants, data scientists, data analysts, software engineers, media traders)
• Develop robust, industry-leading measurement and analytics projects that enable clients with visibility across physical and digital customer journeys (online and offline)
• Planning, leading and delivering advanced analytics strategy and solutions for clients including e-commerce, 3rd party tool implementations, and advanced modeling.
• Identify and support the delivery of suitable statistical data analysis techniques, to provide recommendations for clients which exceed performance expectations and maximizes ROI
• Explore automation techniques that create efficiencies and improve ROI (both internally and for clients) such as scripting, tool development or better client reporting methods
• Act as an internal consultant on analytics for significant projects, helping other teams to shape the very best solutions
• Lead through the ‘pitch ownership’ and by taking an ‘analytics lead’ role on new business pitches

Data Marketing and Analytics leadership

• Lead data analytics development, defining and communicating a clear strategy for the team and the value it will add to the agency
• Work together with the data consultants to champion analytics development and associated platforms on three fronts – internally to the agency, externally to clients and to represent Artefact’s position to the wider marketing community
• Lead and develop roadmaps for our analytics offering, process, and techniques and develop best practice documentation
• Develop review and sign off processes to ensure analytics work is always of the highest possible quality
• Responsible for Artefact being known as exceptional in analytics in the wider market. Actively seek to build Artefact’s profile within the digital marketing community. 

Qualifications: Education & experience required

Core requirements

• 5+ years of hands-on experience in a data-driven environment.
• Strong expertise in at least one of the following domains:

       ◦  Dashboarding & Data Visualization: Power BI, Looker, Tableau, or Superset.

       ◦  Analytics Engineering: dbt, with experience on BigQuery, Snowflake, or Databricks.

       ◦  Marketing Analytics & Measurement: CDP platforms (Treasure Data, Hightouch, Tealium), MMM, attribution, clean rooms.

       ◦  Low-Code / No-Code Data Science: Dataiku, Copilot Studio, or similar platforms.

• Solid foundation in SQL and Python.
• Familiarity with Git and software engineering fundamentals (versioning, testing, code quality).
• Experience working in cloud environments (GCP, Azure, or AWS).

Nice to have

Experience with generative AI applied to analytics (MCP for BI, conversational data interfaces), exposure to multiple domains above, knowledge of statistics and machine learning fundamentals.

Beyond technical expertise, we value: intellectual curiosity, pragmatism and creativity, ability to bridge business and technical teams, autonomy and reliability, and clear communication to build client trust.

Our recruitment process

1. HR call
2. Technical Interview
3. Use Case Interview
4. Fit Interview

At Artefact, we recruit our employees only on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.