Principal/Senior/Mid/Junior - Data Practitioners

We are the backbone of Aily's "Data-to-Decision" engine. We build and own the complete data lifecycle-from ingestion and transformation to quality and delivery. Our team develops robust APIs and scalable infrastructure that ensure high-quality data is always available for the Aily App and our AI models.

• Which data domains and products do we support?

We operate at the intersection of business and technology, supporting critical domains including Finance, R&D, GTM (Go-to-Market), M&S (Marketing & Sales), and Spend. Our pipelines power the Aily App across multiple tenants, delivering the insights that drive global enterprises in several industries.

• What are our key technical challenges?

• Scale: Managing multi-tenant, config-driven pipelines that adapt to diverse client needs.
• Reliability: Ensuring 24/7 uptime through automated QA, validations, and proactive monitoring.
• Quality: Implementing sophisticated business logic checks to maintain a "Single Source of Truth."
• Governance: Orchestrating complex event-driven and scheduled flows while maintaining strict data security and compliance.

• How do we collaborate? Data is our product. We work as strategic partners:

• With Product: To define and refine features that solve real-world problems.
• With Software Engineering: Establishing clear Data Contracts to ensure seamless integration with the Aily App.
• With ML & Data Scientist: Engineering the high-performance datasets required to transform raw data into measurable AI impact., * 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, * 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

Do you have experience in Machine learning?

Aily Labs is a B2B SaaS company building an AI-powered decision intelligence app for enterprises. Our mobile-first platform combines company data with advanced machine learning, large language models, and agentic AI to give business leaders clear, actionable insights in real time. Instead of traditional dashboards and reports, Aily delivers simple, personalized recommendations that help teams decide and act faster across finance, supply chain, R&D, commercial, and more. The app is designed to be intuitive for end users and easy to integrate for IT, so companies can move from analysis and indecision to confident, data-driven decisions every day. Founded in 2020 in Munich, Aily Labs has grown into a global team of 300+ people across Munich, Barcelona, Madrid, Cluj, and New York. Our mission is to democratize AI in business and enable leaders to Lead Boldly, turning complex data into decisions that drive real, measurable impact. We are looking for Data Practitioners who are passionate about building reliable, scalable data infrastructure that powers AI at scale: people who make data accessible, trustworthy, and ready for ML, ensuring our decision intelligence platform can serve millions of insights every day. Your job is to build the data foundation that makes Aily's AI possible.