MUST HAVES

• 5+ years of engineering and data analytics experience;
• Strong SQL and Python/Scala skills for complex data analysis;
• Hands-on experience building automation tooling and pipelines using Python, Scala, Go, or TypeScript;
• Experience with modern data pipeline and warehouse tools (e.g., Snowflake, Databricks, Spark, AWS Glue);
• Proficiency with declarative data modeling and transformation tools (e.g., DBT, SqlMesh);
• Familiarity with real-time data streaming (e.g., Kafka, Spark);
• Experience configuring and maintaining data orchestration platforms (e.g., Airflow);
• Background working with cloud-based data lakes and secure data practices;
• Ability to work autonomously and drive projects end-to-end;
• Strong bias for simplicity, speed, and avoiding overengineering;
• Upper-intermediate English level.

• Architect, build, and maintain modern and robust real-time and batch data analytics pipelines;
• Develop and maintain declarative data models and transformations;
• Implement data ingestion integrations for streaming and traditional sources such as Postgres, Kafka, and DynamoDB;
• Deploy and configure BI tooling for data analysis;
• Work closely with product, finance, legal, and compliance teams to build dashboards and reports to support business operations, regulatory obligations, and customer needs;
• Establish, communicate, and enforce data governance policies;
• Document and share best practices with regards to schema management, data integrity, availability, and security;
• Protect and limit access to sensitive data by implementing a secure permissioning model and establishing data masking and tokenization processes;
• Identify and communicate data platform needs, including additional tooling and staffing;
• Work with cross-functional teams to define requirements, plan projects, and execute on the plan.