Data Engineer

Leadingnation; Hong Kong; On-site; HKD 480,000 - 800,000; Full time

Job summary

Pattern is seeking a Data Engineer to build real-time, automated data streams and ensure data quality across the data lake and data warehouse. You will collaborate with technology teams and partners to specify data requirements and optimize performance using SQL and Python.

Reporting to the Head of Engineering APAC, you will implement data auditing, triage issues, and drive data architecture initiatives with tools like Kafka, Spark, Hadoop, Airflow, and Snowflake.

Qualifications

• Bachelor’s or Master’s Degree in Data Science, Data Analytics, Information Management, Computer Science, Information Technology, or equivalent professional experience.
• Experience in data engineering
• Working with SQL
• Experience in implementing modern data architecture-based data warehouses
• Experience with data warehouses such as Redshift, BigQuery, or Snowflake and understand data architecture design
• Familiarity with big data tools such as Kafka, Spark, Hadoop
• Strong scripting experience in Python for data pipeline development and automation
• Experience with data orchestration and ETL tools such as Apache Airflow, AWS Glue, or similar platforms
• 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

Responsibilities

• 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 in large-scale data processing workflows; 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 using profiling tools and SQL or other relevant query language.
• 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.

Skills

SQL

Python

Data engineering

ETL concepts

Communication

English proficiency

Education

Bachelor’s or Master’s Degree in Data Science, Data Analytics, Information Management, Computer Science, Information Technology

Tools

Kafka

Spark

Hadoop

Airflow

AWS Glue

Redshift

BigQuery

Snowflake

S3

Lambda

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.

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.

Essential Duties and Responsibilities

• 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 using profiling tools and SQL or other relevant query language.
• 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.

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.
• experiences in data engineering
• working with SQL
• experience in implementing modern data architecture-based data warehouses
• experience working with data warehouses such as Redshift, BigQuery, or Snowflake and understand data architecture design
• Familiarity with big data tools such as Kafka, Spark, Hadoop
• Strong scripting experience in Python or similar languages for data pipeline development and automation
• Experience with data orchestration and ETL tools such as Apache Airflow, AWS Glue, or similar platforms
• 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

Preferred Qualifications

• Experience working with time series databases
• 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
• 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, sex, 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, sex, 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.