Required Skills
Data architecture
data analysis
regulatory compliance
data quality frameworks
scalable data pipelines
data integration
data modeling
PySpark
Spark SQL
Scala
Airflow
Azure Data Factory
ELT pipelines
DBT
software engineering best practices
unit testing
integration testing
IntelliJ
Maven
Git
Docker
AWS
Google Cloud
Azure
EMR
Databricks
Synapse
HDInsight
Kinesis
Spark
Redshift
DynamoDB
Aurora
Postgres
Snowflake
Hive
Jupyter
Zeppelin
Jenkins
Streamsets
Quicksight
Tableau
Looker
agile methodologies
Job Summary
Lead the design and implementation of data architecture and analytics, ensuring regulatory compliance, data quality, and sustainable platform growth. Build scalable data pipelines to integrate and model datasets from diverse sources meeting functional and non-functional requirements. Provide technology, tools, and data support to data engineers and data analysts across teams. Ensure data quality by implementing and monitoring a data quality framework alongside data source teams. Collaborate with data infrastructure teams to identify issues and develop solutions. Work closely with cross-functional stakeholders to understand business needs. Conduct end-to-end data analyses, including data collection, processing, scalable deliverables, and presentations. Foster a data-driven culture within the team and lead impactful data projects organization-wide. Support the growth of the data team by mentoring and attracting exceptional engineers.
Experience
Bachelor’s degree in Computer Science or related field.
Over 4 years of relevant experience as a Data Engineer, developing data platforms, data lakes, and business intelligence solutions.
Strong expertise in building data pipelines using technologies such as PySpark, Spark SQL, and Scala.
Experience with orchestration tools and services like Airflow and Azure Data Factory.
Proven expertise in developing production-level ELT pipelines using DBT.
Deep knowledge of software engineering best practices, including unit testing and integration testing, and familiarity with development tools like IntelliJ, Maven, Git, and Docker.
Experience with major cloud platforms (AWS, Google Cloud, or Azure) and their big data services such as EMR, Databricks, Synapse, HDInsight, and Kinesis.
Proficiency in Spark and AWS technology stacks.
Hands-on experience with various database technologies, including columnar, NoSQL, and relational databases such as Redshift, DynamoDB, Aurora, Postgres, and/or Snowflake.
Familiarity with data modeling and management tools like Hive, Jupyter, Zeppelin, and Databricks.
Experience with orchestration, automation, continuous integration, and delivery frameworks such as Jenkins and Streamsets.
Skilled in reporting systems and visualization tools like Quicksight, Tableau, and Looker.
Experience working in agile development environments.
Job Responsibilities
- Lead the design and implementation of data architecture and analytics to ensure compliance, data quality, and sustainable growth of the platform.
- Build scalable data pipelines to integrate and model datasets from various sources, meeting both functional and non-functional requirements.
- Provide technology, tools, and data support to data engineers and data analysts across teams.
- Implement and monitor a data quality framework in collaboration with data source teams to ensure data accuracy and reliability.
- Collaborate with data infrastructure teams to identify issues and develop effective solutions.
- Work closely with cross-functional stakeholders to understand and address business needs.
- Conduct end-to-end data analyses, including data collection, processing, scalable deliverables, and presentations.
- Foster a data-driven culture within the team and lead impactful data projects across the organization.
- Support the growth and development of the data team by mentoring and attracting top engineering talent.
Job Benefits
- PAC.
- Relocation to Barcelona, Spain.
- Sponsored Visa.
- Competitive salary.
- hybrid work model.
- Professional development opportunities.
- Access to the latest technologies and tools.
- Collaborative and inclusive work environment.
- Opportunities for career growth and leadership development.
Desired Skills
Strong leadership and team management
excellent communication and collaboration skills
problem-solving mindset
experience mentoring junior engineers
knowledge of data governance and security best practices
familiarity with container orchestration tools like Kubernetes
experience with machine learning pipelines
proactive attitude towards continuous learning
ability to translate business needs into technical solutions
experience with CI/CD pipelines beyond Jenkins and Streamsets
knowledge of scripting languages like Python or Bash
understanding of cloud cost optimization strategies
experience working in cross-functional agile teams
ability to drive data culture and change management
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