Mid-Level Data Developer

We are seeking a skilled data professional to design, develop, and maintain scalable data pipelines and cloud-based data infrastructure. In this role, you will help transform complex data into reliable, accessible assets that support analytics and machine learning solutions. You will collaborate with cross-functional teams to strengthen data quality, integrity, and usability across data workflows. The position offers the opportunity to work with modern data engineering technologies and contribute to robust, efficient data platforms. You will also help improve development practices through automation, CI/CD implementation, and clear technical documentation. This is a remote opportunity suited to someone who combines strong technical expertise with effective communication in an international environment.

• Data Pipeline Development: Design, build, and maintain scalable data pipelines and cloud-based infrastructure to support analytics and machine learning use cases.

• Data Quality and Integrity: Integrate data quality practices into pipelines and collaborate with cross-functional teams to ensure data remains reliable, consistent, and usable.

• ETL Automation and CI/CD: Develop and maintain CI/CD pipelines for ETL processes, improving deployment efficiency, reliability, and maintainability.

• Data Modeling and Architecture: Support data architecture and modeling initiatives, including dimensional modeling and data lake and data warehouse implementations.

• Documentation: Maintain clear documentation of data workflows, processes, and architectures to support collaboration and long-term platform sustainability.

• Technical Support: Troubleshoot data-related issues, identify root causes, and implement effective solutions to maintain dependable data operations.

• Continuous Improvement: Contribute to improvements in data engineering practices, performance, scalability, and operational efficiency.

• Professional Experience: Proven experience working with modern cloud-based data engineering stacks and developing data pipelines.

• Databricks: Hands-on experience with the Databricks platform is essential.

• Programming and Data Processing: Practical experience with Python, SQL, and Apache Spark.

• CI/CD and ETL: Experience implementing or maintaining CI/CD pipelines for ETL processes.

• Data Modeling: Strong knowledge of dimensional data modeling principles and practices.

• Data Platforms: Experience implementing or working with data lakes and data warehouses.

• English Proficiency: Advanced English skills across reading, writing, and speaking, enabling effective communication with international teams and stakeholders.

• Collaboration and Problem-Solving: Strong analytical thinking, troubleshooting skills, attention to data quality, and the ability to work effectively with cross-functional teams.

Nice to Have:

• Databricks certification.

• Experience working with international clients.

• Familiarity with Microsoft Azure or AWS cloud services.

• Experience with Power BI.

• Knowledge of data quality practices and frameworks.

• Familiarity with data governance using Unity Catalog.

• Understanding of FinOps principles applied to data platforms and workloads.