StockX

Senior Data Engineer

Bengaluru, Karnataka, India

Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
E-commerce, Retail, BiotechnologyIndustries

Senior Data Engineer

Position Overview

Help empower our global customers to connect to culture through their passions. StockX's Technology Team is on a mission to build the next generation e-commerce platform for the next generation customer. We build world-class, innovative experiences and products that give our users access to the world’s most-coveted products and unlock economic opportunity by turning reselling into a business for anyone. Our team uses cutting-edge technologies that handle massive scale globally. We’re an internet-native, cloud-native company from day 1 - you won’t find legacy technology here. If you’re a curious leader who loves solving problems, wearing multiple hats, and learning new things, join us!

As a Senior Data Engineer, you will be empowered to leverage data to drive amazing customer experiences and business results. You will own the end-to-end development of data engineering solutions to support analytical needs of the business. The ideal candidate will be passionate about working with disparate datasets and be someone who loves to bring data together to answer business questions at speed. You should have deep expertise in the creation and management of datasets and the proven ability to translate the data into meaningful insights through collaboration with analysts, data scientists, and business stakeholders.

Responsibilities

  • Design and build mission-critical data pipelines with a highly scalable distributed architecture, including data ingestion (streaming, events, and batch), data integration, and data curation.
  • Help continually improve ongoing reporting and analysis processes, simplifying self-service support for business stakeholders.
  • Build and support reusable frameworks to ingest, integrate, and provision data.
  • Automate end-to-end data pipelines with metadata, data quality checks, and audits.
  • Build and support a big data platform on the cloud.
  • Define and implement automation of jobs and testing.
  • Optimize data pipelines 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, and business partners, actively participating in design thinking sessions.
  • Participate in design and code reviews.
  • Motivate, coach, and serve as a role model and mentor for other development team associates/members who leverage the platform.

Requirements

  • Minimum of 5 years of experience in data warehouse / data lake technical architecture.
  • 3+ years of experience using programming languages (Python / Scala / Java / C#) to build data pipelines.
  • Minimum 3 years of Big Data and Big Data tools experience 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.
  • Experience with Database Architecture/Schema design.
  • Strong familiarity with batch processing and workflow tools such as 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, with the ability to present complex technical/analytical concepts to executive audiences.
  • 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 on data engineering best practices.
  • Bachelor's degree in Computer Science, or a related technical field.

Nice to Have

  • Master's in Computer Science or related quantitative field.

Company Information

StockX is proud to be a Detroit-based technology leader focused on the large and growing online market.

Skills

Data Pipelines
Distributed Architecture
Data Ingestion
Streaming
Batch Processing
Data Integration
Data Curation
Data Quality Checks
Metadata Management
Automation
Cloud Platforms
Big Data Technologies

StockX

Marketplace for high-demand consumer products

About StockX

StockX operates as an online marketplace for buying and selling high-demand consumer products, with a primary focus on sneakers, streetwear, electronics, collectibles, and luxury items. The platform functions like a stock market, where products have real-time market prices determined by supply and demand, allowing users to see the current value of items and make informed decisions. StockX stands out from competitors by ensuring the authenticity of products through a strict verification process, which builds trust among its users. The company generates revenue by charging transaction fees on sales. Its goal is to provide a transparent and reliable platform for consumers who are interested in limited-edition and hard-to-find items, capitalizing on the growing trend of online shopping.

Detroit, MichiganHeadquarters
2016Year Founded
$481.5MTotal Funding
SECONDARYCompany Stage
Fintech, Consumer GoodsIndustries
1,001-5,000Employees

Benefits

Health Insurance
Dental Insurance
Hybrid Work Options
Company Equity
Performance Bonus

Risks

Increased competition from AI-based authentication startups could challenge StockX's market position.
Ongoing legal dispute with Nike over counterfeit products could damage StockX's reputation.
Leadership transition to Greg Schwartz as CEO may lead to strategic shifts impacting stability.

Differentiation

StockX offers a 'stock market of things' model for real-time pricing.
The platform ensures authenticity through a rigorous verification process.
StockX provides a personalized sneaker portfolio feature for users.

Upsides

Integration of AI can enhance StockX's verification system and consumer trust.
NFC-enabled tags can improve authenticity and traceability of items sold.
The rise of challenger sneaker brands presents diversification opportunities for StockX.

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