Technical Architect - IDB
Detalhes do emprego
Works From Home 111 Raglan Avenue Apt 1806 Toronto, ON M6C 2K9, CAN Responsible for designing and deploying Delta lakes.Design the data access architecture for API, streaming and bulk data movementWork with customers/technical consultants to devise and recommend big data solution architecture based on requirementsWork closely with o9 Dev, Devops and project teams at all levels to help ensure the success of projectsWrite and produce technical documentation and manual to be provided to customersMentor junior developers in the teamWhat we'll do for you…Tech tools: Complementary Mac or PC laptop.Enjoy yourself: Unlimited paid time off.Flexibility: Work from home two days a week. Get up a bit later, skip the commute and put the time back into your deadlines.Get social: When we work from home, we play from home with fun after-work activities like Friday Socials. If you're in the office, feel free to join these events in person.Flat organization: With a very strong entrepreneurial culture (and no corporate politics).Support network: Work with a team you can learn from and every day.Diversity: We pride ourselves on our international working environment. What you'll have…Education : Master's Degree in Computer Science plus 5 years experience preferred, or a Bachelor's Degree in Computer Science plusExperience : 10/12 years experience required in a similar rolePython and Pyspark proficiencyMore than 5 years of Big Data related DevOps experience, architecting large scale storage, data center and /or globally distributed solutionsExperience designing and deploying production large-scale Hadoop ecosystems.Experience working in Delta Lake/ Databricks.Expertise in Apache Airflow, Nifi, Spark, HBaseStrong experience implementing software and/or solutions in Cloud (Azure, AWS, GCP)Skill : Strong understanding of network configuration, devices, protocols, speeds and optimizationsSignificant previous work with web-based APIs, preferably REST/JSON or XML/SOAPDemonstrated experience implementing big data use-cases, understanding of standard design patterns commonly usedProficiency with OLAP and OLTP modellingShould be familiar with needs of Machine Learning applications
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