The Role This 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 o

📌 Analytics Engineer (Cataluña)
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📍 Cataluña