Senior Data Engineer

Bengaluru, India

Applications have closed

StockX

Buy and sell the hottest sneakers including Adidas Yeezy and Retro Jordans, Supreme streetwear, trading cards, collectibles, designer handbags and luxury watches.

View all jobs at StockX

Help empower our global customers to connect to culture through their passions.

Technology at StockX 

Our 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! 

About the role 

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. 

What you'll do 

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 

About you 

Minimum of 5 years’ experience in data warehouse / data lake technical architecture 

3+ years of experience in using programming languages (Python / Scala / Java / C#) to build data pipelines 

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 

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 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 

Nice to have: 

Masters in Computer Science or related quantitative field 

 

 
 

About Us
StockX is the premier current culture platform for buying and selling authentic, new, sought-after products. Our powerful marketplace connects buyers and sellers for sneakers, apparel, accessories, electronics, collectibles and trading cards around the world. We provide millions of global customers with unprecedented access and market visibility powered by real-time data, allowing them to transact based on true market value. Launched in 2016 in Detroit, Michigan, StockX now employs more than 1,500 people in offices and authentication centers in 11 countries.     We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. This job description is intended to convey information essential to understanding the scope of the job and the general nature and level of work performed by job holders within this job. However, this job description is not intended to be an exhaustive list of qualifications, skills, efforts, duties, responsibilities or working conditions associated with the position. StockX reserves the right to amend this job description at any time.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  3  0  0
Category: Engineering Jobs

Tags: Airflow Architecture AWS Big Data Computer Science Data management Data pipelines Data quality Data warehouse E-commerce Engineering Flink Hadoop Kafka Machine Learning Pipelines Python Scala Spark Streaming Testing

Perks/benefits: Career development Team events

Region: Asia/Pacific
Country: India

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.