Analytics Engineering Lead

We’re looking for an Analytics Engineering Lead to set the direction for analytics engineering at Eneba and help the team deliver trusted, business-ready data. You’ll lead a team of around 10 analytics engineers.

You’ll define what analytics engineering owns and where it is going, connect the team’s work to real business needs, and ensure curated data can be used directly by business teams, BI tools, and AI agents without an analyst in between.

• Create and own the analytics engineering strategy, direction, and goals.
• Lead, coach, and develop a team of around 10 analytics engineers through regular feedback, one-to-ones, performance management, review cycles, and hiring, helping them become increasingly autonomous.
• Establish the analytics data-modeling architecture, engineering principles, quality standards, and ways of working that guide how the team builds and maintains models.
• Ensure analytics engineering work begins with a clear understanding of the business problem and delivers data that people can use with confidence.
• Enable reliable self-service analytics by making curated data usable by business teams, BI tools, and AI agents, with appropriate semantic layers, metrics, discoverability, and governance.
• Evaluate the current analytics landscape and make pragmatic, evidence-based decisions about what should be improved, stopped, rebuilt, or delegated.
• Partner directly with stakeholders across the company, including teams such as Accounting, Payments, and Marketing, as well as senior leaders.
• Build a strong understanding of Eneba’s business and translate varied stakeholder needs into a clear direction for the team.
• Identify and empower technical experts within the existing team to help define and implement engineering standards.
• Evaluate analytics tooling and delegate technical discovery where appropriate, while retaining final ownership of analytics engineering architecture and tooling decisions.

• Proven experience leading and developing data, analytics, or analytics engineering and people-management in product-focused tech companies.
• Experience defining strategy and setting direction for analytics engineering, data modeling, or a closely related function.
• A track record of establishing data-modeling architecture, principles, or standards that guide how other engineers build and maintain models.
• Strong business judgment: you focus on why data is needed and what problem it solves, not only how models are built.
• Strong stakeholder management and communication skills, with proven experience partnering closely with product leadership and representing data in executive-level and cross-functional discussions.
• Ability to form clear, evidence-based opinions, challenge existing approaches, and lead change under sustained pressure including recommending that work be stopped or rebuilt when needed.
• Experience operating in a high-growth, fast-moving organization with low approval layers, where data supports many business functions. Scale-up experience is helpful.
• Working knowledge of SQL and data modeling, hands-on experience with DBT, and familiarity with at least one BI or dashboarding tool.
• Fluent English (business proficiency required)

• Opportunity to join our Employee Stock Options program.
• Opportunity to help scale a unique product.
• Various bonus systems: performance-based, referral, additional paid leave, personal learning budget.
• Paid volunteering opportunities.
• Work location of your choice: office, remote, opportunity to work and travel.
• Personal and professional growth at an exponential rate supported by well-defined feedback and promotion processes.