What You'll Do:
- Design, build, and maintain efficient and scalable ETL pipelines using tools like dbt, Fivetran, and orchestration frameworks such as Airflow.
- Develop and implement robust schema designs and data models that support efficient querying and data integration across the organization.
- Manage and optimize our data warehouse and lakehouse environments on platforms like Snowflake, ensuring data is accessible, reliable, and performant.
- Implement data validation, cleansing, and anomaly detection processes to ensure the integrity and quality of our data.
- Collaborate with Data Science and Analytics teams to support the deployment of ML models in production, including training, inference, and evaluation processes.
- Implement monitoring and observability solutions to maintain the reliability and performance of data pipelines and models in production.
- Leverage Docker, Kubernetes, and workflow management systems to ensure scalable and automated data processing workflows.
- Ensure compliance with data governance standards and regulations, including GDPR and CCPA, through proper data lineage tracking, metadata management, and secure data handling practices.
Knowledge Requirements:
- MSc/PhD in Computer Science, or a related field
- 5+ years of experience in data engineering, with a strong focus on building and managing data pipelines, data warehouses, and big data platforms.
- Expert in Python and SQL, and experience with data technologies (Kafka, Spark, Hive/Iceberg, Postgres, Redis) and cloud infrastructure (GCP, AWS) is required.
- Proficiency in orchestration and workflow management tools like Airflow, with experience in container orchestration such as Kubernetes being a plus.
- Strong understanding of data quality management practices, data lineage, metadata management, and compliance with regulations like GDPR and CCPA.
- Proven ability to work closely with Data Science and Analytics, and other cross-functional teams to deliver data solutions aligned with business needs.
- Ability to lead data projects independently, make strategic infrastructure decisions, and stay updated with the latest data engineering technologies and practices.
- Ability to work in a fast paced, dynamic environment where adaptability is imperative.
Salary & Benefits
- $170,000-$225,000
- Medical, Dental, and Vision
- Commuter Benefits
- Life & STD Insurance
- Company match on 401 (k)
- Flexible Time Off (FTO)
- Equity
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