Analytics Engineering Lead

whyhirewrong? • Spain
Relocation
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AI Summary

Design, build, and maintain data infrastructure, pipelines, and self-service tooling for data analysts, scientists, and business stakeholders. Collaborate with cross-functional teams to enable effective data use. Strong Python and SQL skills required.

Key Highlights
Build and maintain ETL and ELT pipelines and DBT models
Work with stakeholders to understand data needs and translate into high-quality data products
Identify gaps and improvement areas across the data ecosystem
Key Responsibilities
Design, build, and maintain reliable, tested, and well-documented ETL and ELT pipelines and DBT models
Work with stakeholders across the business to understand data needs and translate them into high-quality, reusable data products
Identify gaps and improvement areas across the data ecosystem and shape the analytics engineering roadmap
Technical Skills Required
Python SQL DBT Dagster Kubernetes Terraform
Benefits & Perks
Relocation assistance available
Hybrid work model with two days per week in the office

Job Description


The RoleThis is a foundational analytics engineering position within a data platform team that sits at the center of the business. The work involves building and maintaining the data infrastructure, pipelines, and self-service tooling that analysts, data scientists, and business stakeholders rely on daily. The team is building out its analytics engineering function from the ground up, which means real ownership and direct influence over how data flows across the organization.

This role is based in Barcelona, Spain. Relocation assistance is available. The working model is hybrid with two days per week in the office.

What The Work Looks Like Day To Day

  • Design, build, and maintain reliable, tested, and well documented ETL and ELT pipelines and DBT models
  • Work with stakeholders across the business to understand data needs and translate them into high quality, reusable data products
  • Identify gaps and improvement areas across the data ecosystem and shape the analytics engineering roadmap
  • Build and maintain self-service tools and datasets that allow engineers, data scientists, and analysts to get to insights quickly
  • Partner with Product Engineering, Data Science, and Analytics teams to enable effective use of the data platform
  • Investigate and resolve data related bugs and technical issues in platform tooling and DBT models
  • Contribute to and lead cross-team data projects with a focus on reliability, efficiency, and testability

Technical Stack

  • Transformation: DBT (core tooling for this role)
  • Orchestration: Dagster
  • Warehouse: Redshift
  • Language: Python (primary), SQL (advanced)
  • Infrastructure: Kubernetes, Terraform

What Is Required

  • 4 or more years of experience in data engineering, analytics engineering, BI engineering, software engineering, or data science
  • Strong Python skills with a focus on writing clean, high quality, maintainable code
  • Advanced SQL skills including writing, tuning, and debugging queries against large, multi-source datasets
  • Proven experience building ETL or ELT pipelines that are reliable, monitored, and easy to maintain
  • Experience gathering requirements from stakeholders and translating them into well structured datasets
  • Comfortable communicating and collaborating across both technical and non-technical teams
  • Familiarity with the majority of the tech stack listed above

What Strengthens an ApplicationExperience contributing to or building out an analytics engineering practice, not just inheriting one. Candidates who have thought about data modeling standards, documentation culture, and self-service enablement alongside pipeline engineering will stand out. Ownership mindset matters as much as technical depth here.

Working Model and LocationThis role is based in Barcelona, Spain, working hybrid with two fixed office days per week (Mondays and Thursdays) at the office. Relocation assistance is available for candidates moving to Barcelona. Full remote is not available for this position. Please submit your CV in English.

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