Senior Data Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 5d ago
The date the source published, not the day we noticed it (2026-10-27). Last seen at its source 1h ago.
We have tracked this listing since 27 Oct 2026 (5 days). The employer's own board has carried it every time we have read it, most recently 1 hour ago.
Is it remote?
The listing says yes
The location field doesn't say remote, so our assessment is based on the title or the description. Read the listing before applying.
Who may apply?
Spain
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay €103.4k–125.4k/yr
Middle 50% of 43 listings that do state pay — Engineering · Senior · Spain · EUR/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Greenhouse employer's own board first seen 5d ago · last seen 1h ago
The listing
Senior Data Engineer
Location: Remote, Barcelona
We are: Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact.
With the right people and the right ideas, there’s no limit to what we can achieve.
Are you a fit? Sounds awesome, right? Now, let’s make sure you’re a good fit for the role:
Key Responsibilities
- Lead the end-to-end, greenfield design and implementation of a scalable cloud data platform—from an empty account to a fully functional production environment.
- Deploy and manage all infrastructure as code (Terraform) through CI/CD pipelines, ensuring robust private networking, least-privilege access, and cost-conscious architecture.
- Build and own complex data transformation models and a unified semantic layer to ensure metrics are defined once and served consistently to both BI tools and AI assistants.
- Design secure, incremental data ingestion pipelines across various complex systems (e.g., HR, Atlassian, GitHub, Finance) that do not natively join.
- Enforce strict privacy by design, implementing row- and column-level access policies on confidential data strictly as code.
- Document architectural decisions (ADRs) clearly and create comprehensive handover documentation to ensure the platform can be easily operated by others.
Must-have Skills
- Experience: 8+ years of data engineering experience, including a proven track record of building at least one production-grade data platform from scratch (not just inheriting one).
- Language: Professional communication skills in English.
- Core Engineering: Advanced SQL and strong Python programming skills, with deep expertise in dimensional modeling and resilient production pipelines.
- Cloud & Infrastructure: Hands-on experience with AWS (S3, IAM, VPC, ECS/Lambda, RDS/Aurora) and deploying Infrastructure as Code using Terraform.
- Data Transformation & Governance: Strong production experience with dbt (tests, documentation, lineage) and a solid understanding of implementing entity resolution and security access policies as code.
Nice-to-have:
- AI Tooling Proficiency: Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows. (This is NOT AN EXAMPLE, INCLUDE IT IN EVERY JOB POSTING)
- Experience with modern enterprise cloud data warehouses (e.g., Snowflake, Redshift Serverless) and semantic/metrics layers (e.g., Cube, MetricFlow, LookML).
- Familiarity with exposing governed data to LLM agents (MCP, tool calling) and evaluating AI-generated answers.
- Previous experience handling cross-system business domains, such as Atlassian data models, GitHub engineering-flow metrics, or enterprise finance/OPEX data.
What we offer:
- A High-Impact Environment
- Commitment to Professional Development
- Flexible and Collaborative Culture
- Global Opportunities
- Vibrant Community
- Total Rewards *Specific benefits are determined by the employment type and location.
Find out more about our culture here.