Senior Data Engineer
New
Spain; Fully remote work across Europe and the UK, flexible collaboration hoursFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 6+ years
- Required Skills
- PythonSQLApache AirflowETLSnowflakeCI/CDdbtGitHub Actions
Requirements
- 6+ years of experience in data engineering or platform engineering roles with strong production system exposure.
- Advanced Python skills, including API clients, data processing, schema validation, and integration logic development.
- Deep expertise with Apache Airflow, including DAG design, dynamic workflows, sensors, retries, backfills, and operational best practices.
- Strong experience with dbt for building modular data transformations (bronze/silver layers, testing, and materialization strategies).
- Solid knowledge of Snowflake, including external stages, data loading patterns, and performance optimization.
- Proven experience integrating external APIs, handling authentication (OAuth, API keys), rate limits, retries, and failure scenarios.
- Experience building reusable data pipelines or framework-style ingestion systems used by multiple teams.
- Hands-on experience with reverse ETL or outbound data activation into external systems.
- Familiarity with CI/CD pipelines (e.g., GitHub Actions) and strong documentation practices.
Responsibilities
- Design and implement scalable data ingestion pipelines using Python, integrating REST APIs, databases, and external data sources into the platform.
- Own end-to-end ETL and reverse ETL processes, including deployment, monitoring, incident resolution, and ongoing reliability improvements.
- Build and evolve reusable ingestion frameworks and pipeline templates that enable new data sources to be onboarded in days instead of months.
- Design and manage orchestration patterns using Apache Airflow, including DAG structure, dependencies, retries, backfills, and dynamic pipeline generation.
- Implement robust API integrations, including authentication flows, token refresh mechanisms, pagination handling, rate limiting, and error classification strategies.
- Ensure high data quality and reliability through automated testing, validation frameworks, and monitoring of production systems.
- Collaborate closely with engineering, product, and data teams to ensure seamless data delivery to downstream systems such as ESPs and marketing platforms.
- Contribute to infrastructure evolution, CI/CD improvements, and Infrastructure-as-Code initiatives, while documenting architectural decisions.
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