---
title: "Mid Data Engineer (Barcelona hybrid)"
company: "WIZELINE"
company_url: "https://www.remjobs.works/companies/wizeline"
url: "https://www.remjobs.works/job/wizeline-mid-data-engineer-barcelona-hybrid-b40873c7-e882-49bf-ab67-074f32ee20ed"
apply_url: "https://www.wizeline.ai/careers/job?gh_jid=7475540"
workplace: onsite
location: "Barcelona"
employment_type: unspecified
seniority: mid
role: data
region: europe
skills: ["airflow", "aws", "databricks", "dbt", "python", "snowflake", "spark", "sql"]
date_posted: 2025-12-16T13:38:57.000Z
first_seen_by_remjobs: 2026-09-15T16:34:55.874Z
---

# Mid Data Engineer (Barcelona hybrid)

**WIZELINE** · Barcelona

Apply: https://www.wizeline.ai/careers/job?gh_jid=7475540

## About WIZELINE

Wizeline accelerates your roadmap through nearshoring and expert AI advisory services, improving efficiency, speeding execution, and driving sustainable innovation.

## About the role

**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:

**Responsibilities:**

**Existing platform (Databricks)**

- Keep production pipelines running: ingestion, transformation, and delivery to downstream consumers.

- Diagnose and resolve pipeline failures and data quality issues, often without documentation to fall back on.

- Reverse-engineer and document existing transformation logic and business rules — this is the input the migration depends on.

- Migrate legacy tables from Hive Metastore to Unity Catalog.

- Maintain Iceberg-enabled table sharing between Databricks and Snowflake.

**New development (Snowflake, dbt, Airflow)**

- Build and test dbt models, including incremental materializations and data tests.

- Develop and maintain Airflow DAGs for orchestration.

- Validate that migrated pipelines produce output equivalent to the Databricks versions.

- Contribute to Snowflake modeling, performance, and cost decisions.

**Across both**

- Work directly with client stakeholders on technical topics, alongside the team lead.

**Technical Requirements**

**Databricks**

- PySpark and SQL — able to read, debug, and modify existing pipelines. Deep Spark tuning is not required.

- Delta Lake: MERGE/upsert patterns, table properties, OPTIMIZE, partitioning.

- Databricks Workflows, cluster configuration, job troubleshooting.

- Unity Catalog: catalogs, schemas, grants, lineage, and the metastore model.

**Snowflake**

- Warehouses, roles and grants, and the general operating model.

- Query performance and an awareness of how compute cost behaves.

**Dbt**

- Models, sources, tests, and incremental materializations.

- Project structure and how dbt fits into a deployment workflow.

**Airflow**

- Writing and maintaining DAGs, operators, scheduling, and dependency management.

- Understanding retries, backfills, and idempotent task design.

**Fundamentals**

- 3+ years operating production data pipelines.

- Strong SQL — window functions, complex joins, reading transformation logic written by someone else.

- Python for scripting, automation, and API integration.

- Incremental loading patterns, idempotency, late-arriving data, reprocessing.

- AWS: S3, IAM basics. Basic working knowledge of Redshift and its role in the wider architecture.

**Ways of working**

- Fluent English — client-facing role with stakeholders based abroad.

- Self-directed. Able to make progress on an unfamiliar codebase without a structured onboarding path, and comfortable asking good questions when context is missing.

- Clear communicator: can explain a production incident to a non-technical stakeholder and give a realistic ETA.

***Nice-to-have:***

- Experience with an actual platform migration, not only greenfield work.

- Open table formats, particularly Iceberg and cross-platform sharing.

- Clickstream or web analytics data (Adobe Analytics, Google Analytics, Segment).

- Experience taking over an undocumented system and stabilizing it.

- 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. 

**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](https://www.instagram.com/wizelineglobal/).

---

Source: WIZELINE's own career page, read by RemJobs. Canonical HTML version: https://www.remjobs.works/job/wizeline-mid-data-engineer-barcelona-hybrid-b40873c7-e882-49bf-ab67-074f32ee20ed