Senior Software Engineer - Data Platform Team

About the Role

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 Senior Software Engineer. 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: 

• Solving zero-to-one or one-to-million problems
• Growing into a Staff / technical leadership role

• Positioning yourself to be a founding engineer for a new team.

What you will do 

• Optimize the performance of offline data processing systems (we use PySpark and Databricks) to increase their efficiency.
• Improve the reliability and security posture of offline data storage systems.
• Define and deliver our data platform offerings across AWS, Azure to empower and delight our internal engineering customers (Data Science and ML)

Must Haves 

• 5+ years of experience working on data-intensive applications and distributed systems. This is not a Data Engineering role. 
• Strong programming skills in Python, Golang, or similar languages.
• Depth in at least one key area of the Data Platform tech stack - batch processing systems (we use Spark), data modeling (DBT), data orchestration systems (such as Airflow)Relational DBs, key value and/or document datastores, caches, Kafka, Spark (or other batch processing systems)
• Excellent ability and strong desire to onboard and mentor other engineers.
• Experience in working with AWS (or a similar public commercial cloud such as Azure / GCP).

Nice to Haves

• Prior experience in up-leveling the use of Spark (or similar data processing systems) in a tech startup to support their growth and scale.
• Prior experience with Databricks.

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