Senior Data Engineer in Apply Digital Latam

ABOUT APPLY DIGITAL

Apply Digital is a global digital transformation partner for change agents. Leveraging expertise that spans Business Transformation Strategy, Product Design & Development, Commerce, Platform Engineering, Data Intelligence, Change Management, and beyond, we enable our clients to modernize their organizations and deliver meaningful impact to the business and to their customers. Our 650+ team members have helped transform global companies like Kraft Heinz, NFL, Moderna, Lululemon, Games Workshop, Atlassian, and The Very Group. Visit applydigital.com to learn how we can unlock your company’s potential.

If you'd like to learn more about Apply Digital's culture click HERE.

LOCATION: Apply Digital is hybrid/remote-friendly. The preferred candidate should be based in Latin America, preferably working in hours that align to ET (Eastern Timezone) or PT (Pacific Timezone).

• Design, build, and optimize ETL/ELT pipelines using Python and SQL
• Develop and maintain data warehouse schemas and analytics solutions
• Implement data models and ensure data quality, consistency, and integrity
• Leverage cloud data platforms (e.g., AWS Athena, Databricks, Snowflake, Azure Synapse/Fabric, Google BigQuery) for storage, processing, and querying
• Create and maintain optimal data pipeline architecture.
• Collaborate with analysts and stakeholders to define requirements and deliver data solutions that meet business needs
• Communicate with stakeholders to understand data requirements and develop solutions.
• Design, develop, implement, and maintain data architectures and pipelines.
• Optimize query performance and ensure efficient data workflowsDocument data pipelines, architectures, and processes
• Continuously improve and refine existing data infrastructure and solution
• Develop and implement best practices for data management, security, and privacy.

• A Bachelor's degree in Computer Science, Information Systems, or a related field.
• At least 5 years of experience in data engineering or related fields.
• Strong expertise in SQL, ETL, and data warehousing technologies.
• Strong working knowledge of Python and PySpark
• Proven experience with at least one major cloud data platform (AWS Athena, Databricks, Snowflake, Azure Synapse/Fabric, or Google BigQuery)
• Knowledge of data migration tools and techniques.
• Good knowledge of databases.
• Strong background in data warehouse design, ETL/ELT processes, and data modeling, ideally with modern data warehouse and DBT
• Familiarity with cloud engineering concepts and best practices
• Experience working with large datasets and optimizing performance
• Excellent problem-solving skills and attention to detail
• Outstanding communication skills in English, both written and verbal.

• Knowledge of multiple cloud platforms (AWS, Azure, GCP) and their data services
• Familiarity with data governance and compliance requirements
• Knowledge of CI/CD practices for data engineering
• Familiarity with Agile development methodologies
• Experience with containerization (Docker, Kubernetes)