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Marketing Technology (MarTech), AdTech, Data Analytics

Staff Software Engineer

San Francisco, California, United StatesOnsiteFull TimeStaff$213,512–$213,512 /yrPosted 1 month agoVisa sponsorship available

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### Who you are
- Bachelor's degree in Computer Science and Engineering or Engineering plus 5 years of experience in the job offered or similar occupation. Employer will accept three or four year bachelor's degree

### What the job involves
- Staff Software Engineer wanted in San Francisco, CA to provide technical guidance to the group responsible for architecting, developing, and owning the company’s marketing platform. Collaborate with Engineers, Product Managers and Executives across the organization to develop a roadmap and subsequent projects to build the next generation comprehensive, multichannel marketing solution that unifies and unlocks data across digital touch points, driving return on marketing investment
- Oversee the design and development of the marketing platform, working on technology that enables access to core of CRM and Data Cloud efforts
- Work with an organization of developers through knowledge sharing sessions that will guide and strengthen their knowledge
- Use distributed systems and cloud architecture
- Architect the company’s big data platform
- Own balancing of production features support, feature delivery and retirement of technical debt
- Build reliable, self-healing services with robust error handling
- Design, develop, debug and operate resilient distributed systems that run across hundreds of compute nodes in multiple data centers
- Drive and deliver thin slices of end-to-end functionality on a regular cadence with data-driven feedback loops
- Build distributed systems, RESTful web-services, microservices
- Own and operate multiple instances of mission critical service
- Use Agile development methodology and test-driven development
- Build real-time streaming data pipelines that scale horizontally
- Use technologies for building real time data pipelines and streaming applications such as Kafka and Amazon Kinesis
- Use NoSQL databases such as Aerospike and data warehouses such as Snowflake/BigQuery
- Use AWS, OpenStack or Azure for scaling web application backend infrastructure

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