What You'll Do:
- Lead, mentor, and grow a high-performing data engineering team, fostering collaboration, innovation, and continuous learning to meet evolving business needs.
- Define and drive the data infrastructure strategy, ensuring alignment with business goals, scalability, and adaptability to support data-driven decision-making and AI/ML initiatives.
- Own the management and optimization of data warehouses and lakehouse (e.g., Snowflake), ensuring data is reliable, performant, and accessible for stakeholders.
- Collaborate with cross-functional leaders (e.g., Data Science, Product, Analytics) to build data foundations that support machine learning, analytics, and business intelligence efforts.
- Ensure best practices in data governance, security, and compliance (GDPR, CCPA), managing data quality, lineage, and security frameworks across all platforms.
- Develop efficient data models and schema designs to support data integration and querying, ensuring scalability and performance across business functions.
- Design and maintain scalable ETL pipelines using tools like dbt, Fivetran, and Airflow, with a focus on real-time processing and automation.
- Leverage Docker, Kubernetes, and automation tools to streamline data processing workflows and ensure efficient resource utilization across the data platform.
- Establish a robust operational framework, including monitoring, alerting, and incident management, to ensure the stability and performance of data platforms in production environments.
Knowledge Requirements:
- MSc/PhD in Computer Science or a related field.
- 10+ years of experience building and managing data infrastructure, with expertise in data pipelines, cloud platforms, and big data technologies.
- Expert in Python, SQL, and big data tools (Kafka, Spark, Hive/Iceberg), with significant experience in cloud platforms (AWS, GCP, Azure).
- Proven experience with containerization (Docker, Kubernetes) and orchestration tools like Airflow to scale and optimize workflows.
- Strong understanding of data quality management, governance, and regulatory compliance, with experience in GDPR and CCPA requirements.
- Demonstrated ability to collaborate with cross-functional teams, including Data Science and ML teams, to deliver data solutions aligned with AI/ML and business objectives.
- Leadership experience managing data engineering teams, driving strategic decisions, and adapting to the latest advancements in data technologies.
Salary & Benefits
- $175,000-$225,000
- Medical, Dental, and Vision
- Commuter Benefits
- Life & STD Insurance
- Company match on 401 (k)
- Flexible Time Off (FTO)
- Equity
0 applies
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