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Responsibilities :
- Design, develop, and maintain large-scale ETL (Extract, Transform, Load) and ELT pipelines using Databricks and PySpark to process vast datasets from various sources.
- Implement data transformations, aggregations, and quality checks to ensure data accuracy and consistency.
- Optimize existing data pipelines for performance, scalability, and cost-efficiency.
Data Warehousing :
- Design, implement, and maintain data warehousing solutions, potentially leveraging Delta Lake or other data lakehouse architectures within Databricks .
- Ensure proper data modeling, schema design, and indexing for optimal query performance.
Advanced SQL Development :
- Write and optimize complex SQL queries for data extraction, manipulation, and analysis.
- Develop stored procedures, functions, and views to support data consumption.
- Implement and manage CI / CD (Continuous Integration / Continuous Deployment) pipelines for data solutions, ensuring automated testing, deployment, and version control.
- Collaborate with DevOps teams to streamline the deployment process and maintain production stability.
Data Quality & Governance :
- Implement data quality checks and monitoring mechanisms to ensure the reliability and integrity of data assets.
- Adhere to data governance policies and best practices.
- Collaborate closely with data scientists, data analysts, and other engineers to understand data requirements and deliver effective solutions.
- Create comprehensive technical documentation for data pipelines, data models, and processes.
Troubleshooting & Support :
- Provide support for production data pipelines, identifying and resolving data-related issues in a timely manner.
Mandatory Skills & Experience :
- Databricks : Strong hands-on experience with Databricks platform, including notebooks, jobs, and the Databricks Lakehouse architecture.
- PySpark : Expert-level proficiency in PySpark for large-scale data processing and transformation.
- Advanced SQL : Demonstrated ability to write and optimize complex SQL queries.
- ETL & Large Dataset Pipelines : Experience building and maintaining robust ETL / ELT pipelines for large datasets.
- Data Warehousing : Practical knowledge of data warehousing concepts, including dimensional modeling (star / snowflake schemas).
- CI / CD Pipelines : Experience implementing and managing CI / CD pipelines (e.g., Jenkins, Azure DevOps, GitLab CI).
- Version Control : Proficiency with tools like Git.
Qualifications :
- Bachelor's degree in Computer Science, Engineering, or a related quantitative field.
- Ideally 5+ years of experience as a Data Engineer.
- Comfortable with mostly remote work and occasional onsite presence in Barcelona.
- Strong analytical, communication, and problem-solving skills.
- Self-motivated and quality-focused.
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Contract
Job function
Job function
Information Technology
Business Consulting and Services
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