Enterprises of all sizes trust Abnormal Security's cloud products to stop cybercrime. These products are data intensive SaaS applications that depend on reliable, scalable, and secure access to data. This is where our Data Platform team fits in, enabling efficient, reliable and scalable data processing across both realtime and offline processing systems. Come empower the rest of engineering to stop cybercrime as we expand our offerings across both clouds and regions.
The Data Platform team is looking to add a Software Engineer II. The individual in this role will have the opportunity to partner closely with our existing world class team of engineers as we define and build the next generation data platform.
There are a lot of opportunities for growth and career advancement – it's up to you to own your career here. Some potential career paths for this role include:
- Growing into a Senior Software Engineer role.
- Positioning yourself to be a founding engineer for a new team.
- Build online and offline data platform offerings across AWS, Azure to empower and delight our internal engineering customers.
- Optimize the performance of existing offline (Spark) and online (DBs, ElasticSearch, Kafka etc) usage to increase efficiency.
- Provide guidance and support to internal engineering teams in their use of the data systems.
- Scale and optimize our overall data center capacity by developing cutting edge Analytics software solutions which improve efficiency and bring automation to our data centers.
- 3+ years of experience as a Back-end Software Developer.
- Strong foundation as a software engineer, able to write clean and testable code.
- Experience in building and operating distributed systems in a high-scale environment.
- Experience with (or interested to learn) Abnormal Security tech stack: Python, Golang, Django, Celery, Postgresql, Redis, Kafka, OpenSearch, AWS / Azure, Terraform.
- Experience working in a Platform / DevEx / Infra team serving the needs of multiple engineering teams.
- Demonstrated excellence in at least one key area of the Data Platform tech stack - relational DBs, RocksDB, ElasticSearch, Redis, Kafka, Spark.
#LI-RT1