OpenMail is an organization centered around data and data products. We firmly believe data should inform and guide every quantitative decision process.
We are building exciting new data products and a state-of-the-art data platform aimed at large scale data collection. At the same time we are building novel approaches to analyze such data and extract knowledge from it in the form of machine learning algorithms. This enables our platform to optimize our users’ experience through product recommendations highly customized to individual preferences and interests.
Our Data Platform team is pragmatic and focused on applying the best tools and development practices. Knowledge essential for this role includes RESTful APIs, relational database technologies like Postgres and MySQL, as well as Amazon AWS technologies like SQS, SNS, Lambda, Kinesis, and Redshift. Of great value is also interest in NoSQL frameworks, like Dynamo, MapReduce, Spark, as tools to address some of the scalability requirements of our platform.
The engineering team as a whole, and the Data Platform team in particular have an open culture and work in an agile style. The ideal candidate for this role will manifest a passion for distributed data platforms and scalable data architectures. In this role, you will be entrusted with the entire end-to-end engineering processes to manage rich datasets from tens of millions of visitors per month. We are looking for self-motivated, creative thinkers, people who are flexible and enjoy working as a team.
- Bachelor’s in Computer Science or equivalent
- 1+ years of experience with Python development
- Working with large SQL datastores to answer business intelligence questions using PostgreSQL & Redshift
- Experience with Linux, the bash shell, Docker and AWS infrastructure
- Working knowledge of web browsers, cookies, fingerprinting, and how these technologies fit in online advertising
- Understanding of NoSQL datastores like DynamoDB and Redis
- Knowledge of queueing systems like SQS and Kinesis Firehose
- Understanding of how to build RESTful APIs
- Create/build/maintain a coherent and performant data architecture
- Prototype, develop, deploy and debug data ingestions and data management services
- Participate in peer code reviews and produce high quality documentation
- Construct queries and reports to guide architectural design, business decisions and optimization algorithms
- Be embedded within the Data Science team and aid in identifying and exploiting patterns and trends
- Take projects through the full engineering lifecycle: designing, ticketing, building, testing, deploying and debugging tools and products
- Help grow a team and work with a tight knit group of engineers and data stakeholders
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