Senior Data Engineer

Pattern is a leading eCommerce data and growth company located in the Silicon Slopes tech hub with global offices in Europe, China, Australia, the Middle East, and Canada. Named one of the fastest-growing companies in the US by Inc. 500, Pattern has made its mark in the industry. Some of the biggest consumer brands like Skullcandy, Nestle, Clorox, Kong, Panasonic, Tumi, and PopSockets trust Pattern with their business. Pattern has recruited talent from brands like Amazon, eBay, Adobe, Pepsico, Apple, Google, and Oracle.

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 Degree in Data Science, Data Analytics, Information Management, Computer Science, Information Technology, related field, or equivalent professional experience
• Overall experience should be more than 7 + years
• 3+ years of experience working with SQL
• 3+ years of experience in implementing modern data architecture-based data warehouses
• 2+ years of experience working with data warehouses such as Redshift, BigQuery, or Snowflake and understand data architecture design
• Excellent software engineering and scripting knowledge
• Strong communication skills (both in presentation and comprehension) along with the aptitude for thought leadership in data management and analytics
• Expertise with data systems working with massive data sets from various data sources
• Ability to lead a team of Data Engineers

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