Staff Data Engineer

As a Staff Data Engineer at Pattern, you will play a crucial role in designing and scaling the canonical data model to ensure the delivery of trusted, high-quality data. Your primary focus will be on transforming complex, raw data into easily understandable tables that power analytics, forecasting, and AI/ML applications. With your technical expertise, you will lead the Patterns Data Engineering team by guiding technical direction, mentoring engineers, and establishing a single source of truth that drives Patterns" global growth. **Roles and Responsibilities:** - Design and evolve canonical and medallion-layer data models (bronze/silver/gold) to enable scalable, governed data across the organization. - Build and optimize ETL/ELT pipelines using Apache Airflow, Spark, Trino, and cloud-native tools. - Develop high-performance data marts and semantic layers to meet the analytics and data science requirements. - Architect streaming and analytical systems utilizing Kafka and ClickHouse for real-time and batch insights. - Define and enforce standards for data modeling, documentation, quality, and lineage across all domains. - Collaborate with Analytics, AI/ML, and Infrastructure teams to transform business logic into reusable, trusted data assets. - Mentor engineers, lead design reviews, and drive continuous improvement in scalability and data reliability. - Promote a culture of data clarity, consistency, and craftsmanship, aligning systems with business goals. **Technical Qualifications:** - Bachelors or Masters degree in Computer Science, Data Engineering, or a related field. - 10+ years of experience in Data Engineering, including 2+ years in a senior or staff-level technical role. - Expertise in SQL, data modeling, and data mart design. - Hands-on experience with Apache Airflow, dbt, Spark, Kafka, and ClickHouse. - Proven track record in designing medallion data architectures and scalable data lakehouse solutions. - Proficiency in Python or Scala, and familiarity with AWS, GCP, or Azure data ecosystems. - Strong understanding of data governance, lineage, and quality frameworks. - Ability to mentor engineers and influence architectural strategy across teams. - Experience with real-time or streaming data (Kafka, Kinesis, or Pub/Sub). - Knowledge of data observability and catalog tools (DataHub, Amundsen, Monte Carlo, Great Expectations, or Soda). - Exposure to eCommerce, retail analytics, or digital marketplaces. - Familiarity with governed data contracts and semantic layer frameworks. - Contributions to open-source data tools or engagement in data community initiatives. **Additional Details:** Pattern is a rapidly growing company with immense opportunities for professional development. Joining our team means being part of a dynamic environment with significant room for personal and career growth.,