At Airalo, we're making it easier for people to stay connected wherever they travel. As the world's first eSIM store, we help millions of travelers access affordable mobile data in 200+ countries and regions around the world.

Today, we're a team of 400+ people across 60+ countries, building a product used by travelers every day. We've grown quickly, but we've worked hard to keep what matters: trust, ownership, and the freedom for people to do great work without unnecessary layers or bureaucracy.

We're fully remote by design, genuinely global, and united by a shared mission to make travel simpler for everyone.

• Location: Remote, anywhere in Spain or the UK.
• Contract:
  • Spain: Full-time, permanent contrato indefinido via Deel (our employer of record in Spain)
  • UK: Full-time, permanent
• Benefits: Learn more about our benefits here in this link - https://airalo-public.notion.site/Benefits-25396a97ffca81fb9bc1f0be479f1be3?pvs=74 
• Languages: English is our main working language day to day, so you'll need to be comfortable communicating in it both in meetings and async.

As the Data Engineering Manager, you will lead the foundational backend of our data organization. You will directly manage our current pod of Data Engineers (2 Senior Data Engineers and 1 Customer Data Platform Engineer) and shape the hiring roadmap as the function grows - including scoping future specialized roles such as Machine Learning Engineers.

Partnering closely with the Data Director, you will help us transition out of the reactive, ad-hoc phase and into a structured, highly scalable data ecosystem. You will own the architecture, ingestion, and orchestration that powers the rest of the data team - ensuring that our Analytics Engineers, Data Analysts and other users have a rock-solid, high-quality foundation to build upon.
This role goes beyond building a data platform. You'll be the connective tissue between Product & Engineering, MarTech, and our partner ecosystem - ensuring data is produced cleanly at the source, captured reliably, and delivered cohesively across the entire organization.

What You Will Do:

• Manage, mentor, and grow a team of senior Data Engineers and CDP Engineers, building a culture of engineering excellence and continuous learning.

  
  

• Drive hiring for the function as it grows, including scoping future specialised roles such as Machine Learning Engineers.

  
  

• Own the DE delivery roadmap — sequencing, prioritisation, trade-offs — in partnership with senior ICs who lead technical direction. Lead delivery of major cross-functional programs as the named DE owner.

  
  

• Represent Data Engineering to the rest of the org — Product, Engineering, Marketing, Finance, and executive stakeholders. Translate between business priorities and engineering reality in both directions, and partner closely with Software Engineering and MarTech on the shared boundary between Data and the rest of the platform.

  
  

• Transition the team's workflow from reactive problem-solving to structured, predictable delivery.

  
  

• Champion high standards on pipeline reliability, observability, data quality, privacy, and governance — owning the prioritisation and follow-through while senior ICs lead the technical implementation.

  
  

• Roll up your sleeves where it helps the team move — complex code reviews, unblocking hard problems, or stepping into hands-on work directly.

  
  

• Act as a strategic partner to the Analytics Engineering Manager and Data Director on the foundations needed for our self-serve analytics ambition and the broader data vision.

  
  
  

Must-haves:

• 7+ years of professional experience as a Data/Software Engineer, with at least 2+ years of experience directly managing and scaling data engineering teams.

  
  

• You thrive in low-maturity or greenfield data environments. You're comfortable navigating ambiguity and enjoy the process of laying down paved roads and engineering standards where none existed before.

  
  

• Deep, hands-on background with major cloud platforms (GCP preferred) and cloud-native data warehouses (BigQuery preferred, or Snowflake/Redshift).

  
  

• Strong experience with orchestration tools (Airflow, Dagster), ELT pipelines (Fivetran, dbt), and distributed data processing frameworks (Apache Spark, Flink).

  
  

• Hands-on experience using AI tools to accelerate engineering workflows - code generation, code review, pipeline debugging, or documentation

  
  

• Strong coding experience in Python (and/or Scala) and advanced SQL across relational and non-relational databases.

  
  

• Experience implementing CI/CD, Infrastructure as Code, and observability/monitoring for data pipelines.

  
  

• Bachelor's degree in Computer Science, Engineering, Statistics, Information Systems, or a related quantitative field.

  
  
  

Nice-to-have:

• Experience implementing data contracts, data catalogues (Atlan, Amundsen, DataHub), or federated governance models.

  
  

• Experience with Customer Data Platforms (Segment, mParticle, or similar), MarTech data integration, and real-time event processing.

  
  

• Experience in marketplace, B2C, or high-volume transactional businesses.

  
  

• Previous work in globally distributed data environments (multi-currency, multi-region, multi-language).

  
  

• Experience building or contributing to experimentation platform infrastructure (A/B testing pipelines, feature flag data, experiment analysis frameworks).

  
  

• Exposure to Machine Learning infrastructure - not necessarily building models, but scoping teams, tooling, and pipelines that support ML workloads.