Principal Data Engineer

Vuori is re-defining what athletic apparel looks like: built to move and sweat in but designed with a casual aesthetic to transition into everyday life. We draw inspiration from an active coastal California lifestyle; an integration of fitness, creative expression and life. Our high energy fast paced retail environment is reflected in the clothes we make. We aim to inspire others to take on all aspects of their lives with clarity, enthusiasm and purpose...while

having a lot of fun along the way. We are proud to be an outlet for opportunity and for personal growth and success.

Vuori is re-defining what athletic apparel looks like: built to move and sweat in but designed with a casual aesthetic to transition into everyday life. We draw inspiration from an active coastal California lifestyle; an integration of fitness, creative expression and life. Our high energy fast paced retail environment is reflected in the clothes we make. We aim to inspire others to take on all aspects of their lives with clarity, enthusiasm and purpose...while

having a lot of fun along the way. We are proud to be an outlet for opportunity and for personal growth and success.

We're looking for a Principal Data Engineer to design, build, and scale the data pipelines that bring data into our platform and make it ready for analytics. You'll work across the full pipeline lifecycle - from raw ingestion of heterogeneous sources through staging and curated layers - while playing a leading role in setting technical direction for our broader data infrastructure.

You'll partner closely with fellow data engineers, data modelers, analysts, and product teams on what gets built next, and help raise the technical bar across the team.

• Move data through the full pipeline lifecycle - raw/src, staging, and curated layers - applying appropriate transformation, validation, and testing at each stage to prepare data for analytics consumption
• Build and maintain Azure Data Factory (ADF) pipelines to orchestrate ingestion and transformation across source, curated, and serving layers
• Design ingestion patterns for a range of raw source formats - REST/SOAP APIs, flat files (CSV, fixed-width), JSON, and XML - landing them reliably into the src layer before transformation
• Build resilient API extraction logic handling pagination, rate limiting, incremental/delta pulls, and schema drift from third-party sources
• Parse and flatten semi-structured JSON payloads (nested objects, arrays) into queryable relational structures within Snowflake
• Handle file-based ingestion at scale - SFTP/blob drops, file validation, schema enforcement, and reprocessing/backfill logic for late or malformed files
• Contribute to ADF pipeline CI/CD, deploying through Azure Dev Ops/Git Hub Actions across dev/UAT/prod environments
• Set technical standards for pipeline design, code quality, and testing, and mentor other data engineers on the team

• Hands-on experience with Azure Data Factory (ADF) - pipelines, data flows, linked services, integration runtimes, and triggers
• Experience extracting and normalizing raw data from heterogeneous sources: REST APIs, flat files, JSON/XML, and SFTP/blob-based drops
• Comfortable writing extraction logic that handles pagination, authentication (API keys, OAuth), and incremental sync patterns
• Experience parsing and modeling semi-structured/nested JSON data within a cloud data warehouse (e.g., Snowflake VARIANT/FLATTEN)
• 8+ years of experience in data engineering or a related field, including experience operating at a senior or technical lead level
• Strong proficiency in SQL and at least one programming language commonly used in data engineering (Python, Scala, or Java)
• Strong communication skills…