Senior Data Engineer

该职位来源于猎聘 Job Description Are you obsessed with data, partner success, taking action, and changing the game? If you have a whole lot of hustle and a touch of nerd, come work with Pattern and use your skills to push one of the fastest-growing companies in the US to the top of the list! Pattern is the premier partner for global ecommerce acceleration and is headquartered in Utah's Silicon Slopes tech hub with offices in Asia, Australia, Europe, the Middle East, and North America. Valued at $2 billion, Pattern has been named one of the fastest-growing tech companies in North America by Deloitte and one of best-led companies in America by Inc. More than 100 global brands like Nestle, Sylvania, Kong, Panasonic, Sorel, Skullcandy, and Popsockets rely on Pattern's global ecommerce acceleration platform to scale their business around the world. Pattern has recruited talent from brands like Amazon, eBay, Adobe, Pepsico, Apple, Google, and Oracle. We're looking for a dynamic, innovative, passionate, highly analytical person to join our development team in Pattern Asian – Guangzhou, China office. This role will report to the Head of Engineering, APAC. Pattern values data and the engineering required to take full advantage of it. As a Data Engineer at Pattern, you will be working on business problems that have a huge impact on how the company maintains our competitive edge.

If this sounds like you, please apply. You’ll be in good company! Essential Duties and Responsibilities Data Engineering

• Develop, deploy, and support real-time, automated, scalable data streams from a variety of sources into the data lake or data warehouse.
• Develop and implement data auditing strategies and processes to ensure data quality; identify and resolve problems associated with large scale data processing workflows; implement technical solutions to maintain data pipeline processes and troubleshoot failures
• Collaborate with technology teams and partners to specify data requirements and provide access to data
• Tune application and query performance (SQL, Spark, Snowflake, etc.) to optimize reporting
• Understand business, operations, and analytics requirements for data
• Build data expertise and own data quality for assigned areas of ownership
• Work with data infrastructure to triage issues and drive to resolution Data Science
• Apply statistical analysis, predictive modeling, and ML techniques (e.g., classification, clustering, time-series forecasting, NLP) to drive insights in sales forecasting, ad optimization, pricing, fraud detection, and customer analytics.
• Partner with product managers and engineers to embed AI/ML models into production systems (recommendation, search, personalization, anomaly detection).
• Lead experimentation frameworks (A/B testing, uplift modeling) and communicate findings with clear business impact.
• Support LLM/AI initiatives by building prototypes, prompt engineering, and data pipelines to enable retrieval-augmented generation (RAG) and AI agent workflows. Required Qualifications
• Bachelor’s or Master’s Degree in Data Science, Data Analytics, Information Management, Computer Science, Information Technology, related field, or equivalent professional experience
• 5+ years of overall experiences in data engineering, with exposure to data science or ML applications
• 3+ years of experience working with SQL
• 3+ years of experience in implementing modern data architecture-based data warehouses
• Experience working with modern data warehouse or lakehouse architectures
• Strong programming skills in Python (pandas, NumPy, scikit-learn, PySpark,

TensorFlow/PyTorch) and SQL.

• Familiarity with big data tools such as Kafka, Spark, Hadoop.
• Excellent software engineering and scripting knowledge
• Strong communication and collaboration skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.
• Expertise with data systems working with massive data sets from various data sources
• Proficiency in reading and writing English is essential
• Ability to design end-to-end ML pipelines from data collection and preprocessing to training, validation, and deployment. Preferred Qualifications
• Experience working with time series databases
• Expertise in time-series forecasting, recommender systems, and NLP
• Advanced knowledge of SQL, including the ability to write stored procedures, triggers, analytic/windowing functions, and tuning
• Advanced knowledge of Snowflake, including the ability to write and orchestrate streams and tasks
• Background in Big Data, non-relational databases, Machine Learning and Data Mining
• Experience with cloud-based technologies including SNS, SQS, SES, S3, Lambda, and Glue
• Experience with modern data platforms like Redshift, Cassandra, DynamoDB, Apache Airflow, Spark, or ElasticSearch
• Familiarity with LLM applications, RAG pipelines, and AI agent frameworks.
• Experience in ecommerce, ad tech, or financial risk modeling domains
• Expertise in Data Quality and Data Governance
• Proficiency in spoken English is preferred What We're About
• Data Fanatics: Our edge is always found in the data
• Partner Obsessed: We are obsessed with partner success
• Team of Doers: We have a bias for action
• Game Changers: We encourage innovation 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, ***, 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. 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, ***, 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.