Data Analytics Engineer

About Jetpac

The Role

What You Will Do

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

Required Skills and Experience

• Require 3–6 years of data engineering or analytics engineering experience with significant data platform ownership.
• Require strong SQL skills and experience designing and optimizing analytical data models.
• Require production ETL/ELT pipeline experience and experience with modern data warehouses such as Snowflake, BigQuery, or Amazon Redshift.
• Require experience with dbt, Apache Airflow, application databases, database migrations, and schema management.
• Require understanding of Bronze/Silver/Gold architectures, dimensional modeling, data quality, lineage, observability, and monitoring.
• Require familiarity with event streaming concepts such as Apache Kafka or similar systems.
• Require experience using AI-assisted tools while maintaining production-quality standards.

Nice to Have

• Experience with Apache Kafka, Amazon Kinesis, or similar event streaming technologies is desirable.
• Experience supporting recommendation engines, personalization, or customer data platforms is desirable.
• Experience in consumer internet, travel, fintech, or marketplace businesses is desirable.

Focus Areas and Outcomes

Team Environment

• The team offers high ownership, low bureaucracy, global product impact, and a fast-moving engineering culture.
• The source describes a flexible work setup across global teams.