Job Description

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 its 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 languages.
• 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