Data Engineer – Platform (Jetpac)

About the role

We’ve reached meaningful scale and are rebuilding key parts of our data platform to support the next phase of growth. You’ll work closely with product, engineering, analytics, and business teams to build the data foundations that power reporting, decision‑making, experimentation, and future data products.

Key responsibilities

• Design, build and maintain ETL/ELT pipelines from operational systems into the data warehouse.
• Build and manage Bronze, Silver, and Gold data layers that power BI dashboards and business reporting.
• Create reliable data models, curated datasets, and semantic layers for analytics and self‑service reporting.
• Own database migrations, schema evolution, and data‑related application changes alongside engineering teams.
• Ensure data quality, observability, performance, and governance across the platform.
• Use AI‑assisted workflows to accelerate data engineering, modeling, and debugging.
• Contribute to event‑streaming, customer‑context, and recommendation‑system foundations as the platform evolves.

Required profile

• 3–6 years of experience in Data Engineering or Analytics Engineering with significant data platform ownership.
• Strong SQL skills with experience designing and optimizing analytical data models.
• Hands‑on experience building and operating production ETL/ELT pipelines.
• Experience with modern data warehouses such as Snowflake, BigQuery, Amazon Redshift, or similar.
• Experience with dbt and Apache Airflow.
• Strong understanding of Bronze/Silver/Gold architectures, dimensional modeling, and analytical data design.
• Experience working with application databases such as PostgreSQL or MySQL.
• Managing database migrations, schema changes, and data consistency across environments.
• Understanding of data quality, lineage, observability, and monitoring.
• Familiarity with event streaming concepts and technologies such as Apache Kafka.
• Experience using AI‑assisted tools to accelerate development while maintaining production‑quality standards.

Required skills

• SQL
• Snowflake
• BigQuery
• Amazon Redshift
• dbt
• Apache Airflow
• PostgreSQL
• MySQL
• Apache Kafka
• AI‑assisted development tools