Data Engineer

About Us:

At Arctic Wolf, we're redefining the cybersecurity landscape. With our employee Pack members, spread out globally, committed to setting new industry standards. Our accomplishments speak for themselves, from our recognition in the Forbes Cloud 100, CNBC Disruptor 50, Fortune Future 50, and Fortune Cyber 60 to winning the 2024 CRN Products of the Year award. We’re proud to be named a Leader in the IDC MarketScape for Worldwide Managed Detection and Response Services and earning a Customers' Choice distinction from Gartner Peer Insights. Our Aurora Platform also received CRN’s Products of the Year award in the inaugural Security Operations Platform category. Join a company that’s not only leading, but also shaping, the future of security operations. 

About the Team:  

Arctic Wolf Labs is the research-focused division at Arctic Wolf focused on advancing innovation in security operations. The mission of Arctic Wolf Labs is to develop cutting-edge technology and tools that are designed to enhance the company’s core mission to end cyber risk, while also bringing comprehensive security intelligence to Arctic Wolf’s customer base and the security community-at-large. Leveraging more than seven trillion security events the Arctic Wolf Security Operations Cloud ingests, parses, enriches, and analyzes each week, Arctic Wolf Labs is responsible for performing threat research on new and emerging adversaries, developing advanced threat detection models, and driving improvement in the speed, scale, and detection abilities of Arctic Wolf’s solution offerings. The Arctic Wolf Labs team comprises security and threat intelligence researchers, data scientists, and security development engineers with deep domain knowledge in artificial intelligence (AI), security R&D, as well as advanced threat offensive and defensive methods and technologies. 

About the Role:

Data is a critical part of Arctic Wolf Network’s mission to solve cyber risk, where we process and analyze hundreds of billions of events every day to look for malicious and risky behavior. Furthermore, we’re geeks at heart and are passionate about data and solving cybersecurity problems for our customers. The AI & Data Science team works on analyzing Arctic Wolf’s product platforms, internal business challenges, and customer pain points to develop new products and features for our customers. 

As a Data Engineer on the AI & Data Science team you will be responsible to create data pipelines for our suite of cybersecurity products and services. They will partner with Data scientists and MLOPs engineers as a data engineer, familiar with SQL, Spark, and either/both of Databricks or Athena/Iceberg/Trino to write and optimize ETL/ELT jobs to ingest raw data from a variety of sources, refine that data, and optimize/tune those datasets into production. They should be comfortable with relational- and non-relational databases like SQL and PostgreSQL, big data systems such as Spark, and cloud-deployments of software and ETL jobs in AWS. Workflow orchestrators such as Airflow will also be used. Knowledge of cybersecurity and data science are a bonus.  

As a Developer – Data Engineer at Arctic Wolf, You Will:   

Execute on R&D of distributed, highly scalable, and fault-tolerant microservices 

Use test-driven development techniques to develop beautiful, efficient, and secure code  

Create and scale high-performance services that bring new capabilities to Arctic Wolf’s data science organizations  

Identify problems proactively and propose novel solutions to solve them  

Continuously learn and expand your technical horizons
 

We're Looking For Someone Who: 

Will collaborate closely with our Data science and Threat Research teams across different cybersecurity domains to define data infrastructure requirements and build critical data services. 

Has proficiency in big data technologies such as Apache Spark, Databricks, Kafka, SQL, Terraform. 

Has experience interacting with and authoring workflows, such as prompts or tools, for LLMs, in AWS Bedrock 

Has experience with data pipelines tools (Flink, Spark or Ray) and orchestration tools such as Airflow, Dagster or Step Functions 

Has knowledge of Data Lake technologies, data storage formats (Parquet, ORC, Avro), and query engines (Athena, Presto, Dremio) and associated concepts for building optimized solutions at scale 

Maintains an expert level in one of the following programming languages or similar- Python, Java, Go, Scala 

Can implement data streaming and event-based data solutions (Kafka, Kinesis, SQS/SNS or the like) 

Has experience deploying software with CI / CD tools including Jenkins, Harness, Terraform etc.  

Has hands-on experience implementing data pipeline infrastructure for data ingestion and transformation near real-time availability of data for applications and ETL pipelines 

Has 2+ years of experience in building and shipping scalable microservices and APIs