Data Tech Lead

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.

Benefits

- Relocation to Barcelona, Spain.
- Sponsored Visa.
- 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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