Data Engineer

About the role

Join our team as a Data Engineer II, where you'll design and scale our modern data platform to support analytics, self-service BI, real-time use cases, and AI-powered insights. You'll work closely with analytics engineers, product teams, and business stakeholders to deliver reliable, high-quality data that drives measurable business outcomes. This hands-on role is ideal for someone who enjoys building Lakehouse-based platforms, enabling streaming data, and supporting AI and GenAI use cases in production. Key missions: Design, build, and operate scalable batch and streaming data pipelines, and implement transformations and analytics-ready datasets using DBT.. Collaborate with analytics engineers, product teams, and business stakeholders to deliver reliable, high-quality data that drives measurable business outcomes.. Support AI and GenAI use cases, including enabling high-quality data access for tools like Databricks Genie, and contribute to data platform standards, documentation, and best practices. Profile: - 5+ years experience in a Data Engineering position - Hands-on experience with Apache Airflow5 - Experience with data ingestion tools such as Fivetran - Strong experience with Python and SQL - Familiarity with AWS services including Athena, EC2, and cloud-based data platforms - Working knowledge of Apache Iceberg and modern Lakehouse architectures - Experience working with Databricks - Experience implementing data quality checks, testing frameworks, and pipeline observability - Expertise using DBT for transformations and analytics modeling - Strong understanding of data modeling, analytics, and semantic layer design - Experience building streaming data pipelines with Kafka - Experience enabling AI or GenAI use cases on top of analytics platforms (e.g., Databricks Genie) - Experience delivering self-service BI solutions (e.g., ThoughtSpot) - Knowledge of data governance, metadata management, and data catalogs - Experience supporting SaaS or multi-product platforms - Familiarity with privacy, compliance, and secure data access patterns