The Role
As a Staff Data Engineer, lead the design and scaling of data models, optimize ETL/ELT pipelines, and mentor engineers while ensuring data quality and governance.
Summary Generated by Built In
Role Overview
As a Staff Data Engineer, you’ll be a technical leader and systems thinker within Pattern’s Data Engineering team—designing and scaling our canonical data model to deliver trusted, high-quality data. You’ll transform complex, raw data with a set of efficient pipelines into tables that are easy to understand and efficient to power analytics, forecasting, and AI/ML. You’ll lead through influence, shaping technical direction, mentoring engineers, and building the “single source of truth” that drives Pattern’s global growth.
Roles and Responsibilities
- Design and evolve canonical and medallion-layer data models (bronze/silver/gold) that 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 that serve analytics and data science needs.
- Architect streaming and analytical systems using Kafka and ClickHouse for real-time and batch insights.
- Define and enforce standards for data modeling, documentation, quality, and lineage across all domains.
- Partner with Analytics, AI/ML, and Infrastructure teams to translate business logic into reusable, trusted data assets.
- Mentor engineers, lead design reviews, and drive continuous improvement in scalability and data reliability.
- Champion a culture of data clarity, consistency, and craftsmanship, aligning systems to business goals.
Required Qualification
- Bachelor’s or Master’s 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.
- Deep hands-on experience with Apache Airflow, dbt, Spark, Kafka, and ClickHouse.
- Proven experience 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.
- Demonstrated ability to mentor engineers and influence architectural strategy across teams.
Preferred Qualification
- 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).
- Experience in eCommerce, retail analytics, or digital marketplaces.
- Exposure to governed data contracts and semantic layer frameworks.
- Proven track record of leading data architecture initiatives or cross-functional platform modernization.
- Contributions to open-source data tools or engagement in data community initiatives
Why Pattern?
- The company is a rocket ship experiencing phenomenal growth
- We have tailwinds and a long runway; we’re barely scratching the surface
- We have big opportunities that will get you energized and excited
Great benefits including time off, insurance, competitive pay
Pattern provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability, status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.
Top Skills
Apache Airflow
AWS
Azure
Clickhouse
Dbt
GCP
Kafka
Python
Scala
Spark
SQL
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The Company
What We Do
Pattern operates as a worldwide e-commerce growth, protection, control, and distribution platform for brands.
Pattern® provides a proven blend of marketplace analytics, product distribution, MAP compliance, and brand management to drive ecommerce acceleration for premium brands. We thrive on high energy, professional excellence, and disciplined creativity.
