Required Skills
Advanced SQL
Expert-level DBT
Python programming
Jinja templating
Apache Airflow
Spark
PySpark
Spark SQL
Scala
Data modeling
Data warehousing
ETL
ELT
AWS (Redshift
EMR
Kinesis
DynamoDB
Aurora)
Snowflake
Git
Docker
Maven
IntelliJ
Unit testing
Integration testing
CI/CD
BI tools
Looker
Power BI
Qlik Sense
Tableau
Quicksight
Agile methodologies
Cross-functional teamwork
Analytical thinking
Problem-solving
Communication skills
Self-driven
Organized
Multitasking
Job Summary
We are looking for a highly skilled and proactive Senior Data Engineer to join a dynamic and cross-functional data team. The ideal candidate will have extensive experience in building and optimizing ELT pipelines using modern tools, ensuring data quality and availability, and supporting business intelligence and analytics initiatives in cloud-based environments.
Experience
4+ years of hands-on experience as a Data Engineer or in a similar role.
Proven experience designing and maintaining production-grade ELT pipelines using DBT (expert level).
Solid background in working with Apache Airflow or other data orchestration tools.
Strong practical experience with Spark technologies (PySpark, Spark SQL, or Scala) for large-scale data processing.
Professional experience with AWS cloud services, especially in big data environments (e.g., EMR, Redshift, Kinesis, DynamoDB, Aurora).
Deep understanding of SQL and working with cloud-based databases (Snowflake is a plus).
Experience integrating and managing data across data lakes, data warehouses, and BI platforms.
Familiarity with unit testing and integration testing in data engineering projects.
Hands-on experience with tools like Git, Docker, Maven, and IntelliJ.
Experience working with BI and reporting tools such as Looker, Power BI, Qlik Sense, Tableau, or Quicksight.
Previous involvement in Agile or Scrum environments, working collaboratively with cross-functional teams.
Job Responsibilities
- Design, develop, and maintain robust, scalable, and efficient ELT data pipelines using DBT and Spark.
- Ensure high data quality, availability, and integrity across data systems and products.
- Manage data orchestration workflows using tools such as Apache Airflow.
- Collaborate closely with data analysts, data scientists, and product teams to understand data requirements and deliver effective solutions.
- Analyze and optimize existing data pipelines and infrastructure for performance and cost-efficiency.
- Build and maintain integrations between various data sources and storage systems (cloud and on-prem).
- Support the development of BI dashboards and reports using tools such as Looker, Power BI, or Tableau.
- Implement and follow best practices in software engineering: version control, documentation, testing (unit/integration), and CI/CD.
- Address data inconsistencies or gaps by proposing and implementing temporary or long-term solutions.
- Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence within the data engineering team.
Job Benefits
- PAC.
- Relocation to Barcelona, Spain.
- Sponsored Visa.
- Hybrid work model.
- Competitive salary.
- Professional development opportunities.
- Modern tech stack and the opportunity to work on high-impact data engineering projects.
- International, cross-functional team and exposure to diverse business domains.
- Collaborative and inclusive work environment with a strong engineering culture.
- career growth.
Desired Skills
Experience with Hive
Databricks
Jupyter
Zeppelin
Google Cloud Platform
Microsoft Azure
Streamsets
Jenkins
Exposure to additional cloud platforms
Familiarity with NoSQL databases
Knowledge of columnar databases
Experience in data visualization beyond BI tools
Advanced automation skills
Prior experience in Agile/Scrum environments
Strong collaboration skills
Ability to mentor junior team members
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