Data Engineer - Pattern

Job Title: Data Engineer
Job Location: Pune, India
Job Listing URL: https://jobs.lever.co/pattern/2956151e-06bd-45bf-ad88-ef4350d9f613
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! We want you to use your skills to push one of the fastest-growing companies headquartered in the US to the top of the list.

Pattern accelerates brands on global ecommerce marketplaces leveraging proprietary technology and AI. Utilizing more than 46 trillion data points, sophisticated machine learning and AI models, Pattern optimizes and automates all levers of ecommerce growth for global brands, including advertising, content management, logistics and fulfillment, pricing, forecasting and customer service. Hundreds of global brands depend on Pattern’s ecommerce acceleration platform every day to drive profitable revenue growth across 60+ global marketplaces—including Amazon, Walmart.com, Target.com, eBay, Tmall, TikTok Shop, JD, and Mercado Libre. To learn more, visit pattern.com or email press@pattern.com.

Pattern has been named one of the fastest growing tech companies headquartered in North America by Deloitte and one of best-led companies by Inc. We place employee experience at the center of our business model and have been recognized as one of Newsweek’s Global Most Loved Workplaces®.

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 4 + 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
Our Core Values
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