About the role

AI is reshaping aviation, and zeroG is at the core of it. We are the AI experts of Lufthansa Group, building human-centric data and AI solutions that solve problems affecting millions of passengers and some of the most complex operations in the world.

We are looking for a Senior Data & Analytics Consultant to join our Decision Analytics Capability Center and work across a portfolio of client engagements. This role is the link between our clients' business questions and the data that answers them, and it's often what decides whether a project actually changes how a client works. You'll own data and analytics initiatives from problem framing through delivery and adoption, with clients that vary in industry, data maturity and need.

In this role, you will

Lead analytics initiatives end to end: define the problem, design the solution, set priorities, deliver and keep stakeholders aligned.
Consult with stakeholders and customers to understand their business needs and translate complex or ambiguous questions into clear analytical approaches and tangible outcomes.
Build the metrics and analytical products that clients use for strategic and operational decisions.
Work hands-on with large, complex datasets and make sure the data is structured and reliable enough to answer business questions.
Spot where data, advanced analytics or automation could improve a process or create new value, and help build the business case for it.
Work with Data Engineers and Data Scientists to move prototypes and PoCs into production, including data pipelines, analytical models and GenAI-enabled solutions where they make sense.
Advise clients on data governance, including data products and data contracts, and help them put it into practice.
Challenge assumptions with data and make sure what you deliver gets adopted and understood.
Mentor junior colleagues through feedback, guidance and knowledge sharing.

What skills should you have?

Consulting and problem-solving

At least four years of experience delivering data, analytics or business intelligence work in client-facing or cross-functional environments.
Strong ability to translate ambiguous business problems into analytical approaches that influence decisions and outcomes.
Experience managing stakeholder relationships across business and technical audiences, including presenting findings, managing expectations and acting as a trusted point of contact.
Comfortable contributing to business cases, scoping analytical work and guiding delivery through ambiguity, including in environments with shifting priorities and varying client maturity.
Experience applying AI and advanced analytics to assess business problems and support decision making, including knowing when these approaches add genuine value and when they do not.

Technical

Advanced proficiency in SQL and solid experience with Python or equivalent for data analysis and manipulation.
Experience working in cloud-based analytics environments. Familiarity with at least one major cloud platform (Azure, GCP or AWS) is expected; breadth across more than one is an advantage.
Solid working knowledge of BI and visualization tools. Experience with Tableau, Power BI or Looker is expected.
Experience working in cloud-based analytics environments. Familiarity with at least one major cloud platform (Azure, GCP or AWS) and a modern data platform (e.g. Databricks, Snowflake) is expected; breadth across more than one is an advantage.

The following skills and experience would also be an asset:

Bonus points for

Experience working in agile environments, including backlog refinement and iterative delivery.
Familiarity with analytics engineering in practice, understanding how data models are structured and how analytical layers are built on top of them.
Comfortable using AI-assisted development tools such as GitHub Copilot or similar to accelerate analytical work.
Familiarity with project planning and collaboration tools such as Jira or Confluence.
Experience leading or contributing to initiatives that move analytical solutions from exploration into production.

What to expect working here

You'll move between client engagements, so the problem, the data environment and the stakeholders will change from one project to the next. What stays the same is how you work: structured thinking, honest client relationships and delivering when things are uncertain. If you'd rather specialize deeply in one tech stack or one product, this probably isn't the right role for you. If you like variety and building expertise across different client contexts, it probably is.