You will

• Design and implement a cloud-based data lakehouse platform ingesting engineering and security telemetry from multiple sources
• Build scalable Bronze/Silver/Gold data layers, ensuring reliable ingestion, transformation, and consumption patterns
• Develop and maintain streaming and batch pipelines using technologies such as Kafka, Flink, Spark Streaming, or Kinesis
• Model complex relationships using graph databases (Neo4j, Neptune, TigerGraph) to support advanced analytics and AI-driven use cases
• Collaborate with data scientists, platform engineers, and security teams to deliver high‑quality, production-grade data solutions
• Implement robust data transformation frameworks (dbt, Databricks SQL, Dataform, or custom SQL/Python pipelines)
• Build and maintain orchestration workflows using Airflow, Prefect, Dagster, Step Functions, or similar tools
• Define and enforce data modeling standards, including dimensional modeling, SCD2, and normalization strategies
• Use Infrastructure as Code (Terraform, CloudFormation, Pulumi) to provision and manage cloud resources
• Ensure observability and reliability of pipelines through monitoring, alerting, and data quality validation
• Work autonomously in a fast‑moving environment, proposing solutions even when requirements are incomplete