Core responsibilities

Junior Data Practitioner – up to ~2 years

• Build and maintain data pipelines and ETL processes for specific datasets or use cases, following existing patterns and guidance.

• Implement and improve data quality checks, monitoring and alerting for assigned datasets.

• Collaborate with Data Scientists and ML Engineers to make data available and usable for model development.

• Deliver assigned data tasks on time with autonomy, showing accountability and a strong “doer” mindset.

• Learn to work with Aily's data stack (warehouse, streaming, orchestration, catalog).

Mid Data Practitioner- 2–4 years of experience

• All of the above +

• Design and implement end-to-end data pipelines (ingestion → transformation → quality → delivery) for multiple use cases with growing autonomy.

• Build and maintain data infrastructure components (streaming pipelines, transformations, APIs, catalogs) using modern data tools.

• Implement robust data quality frameworks, monitoring, and alerting systems at scale.

• Optimize data workflows for cost, performance,e and reliability across multiple datasets.

• Mentor junior team members on data engineering best practices and tooling.

Senior Data Practitioner – 4+ years of experience

• All of the above, plus:

• Lead the design and implementation of complex, scalable data platforms and pipelines that support multiple teams and use cases.

• Drive improvements in data infrastructure, tooling and processes that reduce operational burden and improve data team efficiency.

• Own critical data systems end-to-end, from requirements to production monitoring, with only strategic guidance.

• Establish and enforce data engineering standards (quality, governance, reliability, performance) across the organization.

• Collaborate with ML Engineering, Data Science and Product teams to design data architecture that powers AI at scale.

Principal Data Practitioner – 8+ years of experience

• All of the above +

• Act as technical authority for the Data Platform, deeply understanding Aily's data architecture and shaping long-term data strategy across teams

• Lead cross-team data architecture discussions and technical design sessions, ensuring scalable, future-proof solutions

• Define and maintain org-wide data standards (quality, governance, reliability, performance, security) and drive adoption across all teams

• Own multiple critical data initiatives simultaneously, managing complexity, external stakeholders, and leadership expectations

• Solve org-critical data challenges and represent data engineering standards as the ultimate quality gatekeeper

Who we’re looking for (all levels)

• Data Engineers who excel at building reliable, scalable data infrastructure that powers AI decision-making at enterprise scale.

• Hands-on builders who love creating robust data pipelines, optimizing systems for performance and cost, and ensuring data quality at every step.

• Strong collaborators who partner with Data Scientists, ML Engineers, Product teams, and business stakeholders to turn raw data into actionable insights.

• Startup mindset: thrives in ambiguity, proactively solves complex data challenges, and improves tooling beyond your immediate scope.

• Ready to Lead Boldly – building the data foundation that enables Aily's AI platform to deliver millions of real-time insights daily

Location & details

• Locations: Madrid (MAD), Barcelona (BCN).

• Contract type: Permanent.

• Work policy: hybrid (2 days per week in the office)