Senior Data Engineer
Help empower our global customers to connect to culture through their passions.
- Design and build mission critical data pipelines with a highly scalable distributed architecture - including data ingestion (streaming, events and batch), data integration, data curation
- Help continually improve ongoing reporting and analysis processes, simplifying self-service support for business stakeholders
- Build and support reusable framework to ingest, integration and provision data
- Automation of end to end data pipeline with metadata, data quality checks and audit
- Build and support a big data platform on the cloud
- Define and implement automation of jobs and testing
- Optimize the data pipeline to support ML workloads and use cases
- Support mission critical applications and near real time data needs from the data platform
- Capture and publish metadata and new data to subscribed users
- Work collaboratively with business analysts, product managers, data scientists as well as business partners and actively participate in design thinking session
- Participate in design and code reviews
- Motivate, coach, and serve as a role model and mentor for other development team associates/members that leverage the platform
- Minimum of 5 years' experience in data warehouse / data lake house technical architecture
- 3+ years of experience in using programming languages (Python / Scala / Java / C#)
- Minimum 3 years of Big Data and Big Data tools in one or more of the following: Batch Processing (e.g. Hadoop distributions, Spark), Real time processing (e.g. Kafka, Flink/Spark Streaming)
- Minimum of 2 years' experience with AWS or engineering in other cloud environments
- Strong Knowledge of Databricks SQL/Scala - Data Engineering Pipelines
- Experience with Database Architecture/Schema design
- Strong familiarity with batch processing and workflow tools such as dbt, AirFlow, NiFi
- Ability to work independently with business partners and management to understand their needs and exceed expectations in delivering tools/solutions
- Strong interpersonal, verbal and written communication skills and ability to present complex technical/analytical concepts to executive audience
- Strong business mindset with customer obsession; ability to collaborate with business partners to identify needs and opportunities for improved data management and delivery
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Bachelor's degree in Computer Science, or a related technical field
- Masters in Computer Science or related quantitative field
Pursuant to the various pay transparency laws/acts, the base salary is between $130,000 to $150,000 plus opportunities for benefits (e.g., medical, dental), equity and discretionary bonuses. Compensation is dependent on geography and may vary.
Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.
StockX is proud to be a Detroit-based technology leader focused on the large and growing online market for sneakers, apparel, accessories, electronics, collectibles, trading cards, and more. StockX's powerful platform connects buyers and sellers of high-demand consumer goods from around the world using dynamic pricing mechanics. This approach affords access and market visibility powered by real-time data that empowers buyers and sellers to determine and transact based on market value. The StockX platform features hundreds of brands across verticals including Jordan Brand, adidas, Nike, Supreme, BAPE, Off-White, Louis Vuitton, Gucci; collectibles from brands including LEGO, KAWS, Bearbrick, and Pop Mart; and electronics from industry-leading manufacturers Sony, Microsoft, Meta, and Apple. Launched in 2016, StockX employs 1,000 people across offices and verification centers around the world. Learn more at www.stockx.com.
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