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Open nowPosted 314 days ago

Mid Data Engineer (Barcelona hybrid)

WIZELINE34 open roles

Where
Barcelona
Work mode
Hybrid
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Your applicationOpen nowMid Data Engineer (Barcelona hybrid)WIZELINE · Barcelona

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. WIZELINE postings stay open a median of 33 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 314 days ago

WIZELINE median: 33 days open

The posting

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.

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