Job Title: Principal Data Engineer
Job Summary:
We are seeking an experienced Data Engineer to join our team in building, enhancing, and maintaining scalable data solutions. This role offers an opportunity to work with cutting-edge data processing technologies and contribute significantly to backend development projects.
Key Responsibilities:
- Architect and develop well-designed, testable, efficient, and secure code.
- Analyze complex problems and devise innovative solutions, adapting existing approaches to resolve diverse challenges with limited information.
- Exercise evaluation, judgment, and interpretation to independently select appropriate courses of action, with work reviewed at key milestones.
- Engage in the entire software development lifecycle, including CI/CD processes.
- Mentor and support new and junior team members.
- Creatively assess and resolve a wide range of issues, suggesting alternative approaches as needed.
- Work closely with data consumption stakeholders and display strong analytical knowledge to define data models that are both efficient and cost effective
Work Culture Highlights:
- Sharing Culture: Teams showcase their work during our monthly Platform R&D Demos, fostering department-wide collaboration.
- Annual Hackathon: Participate in a four-day, department-wide Hackathon, teaming up across all R&D teams to innovate and develop new ideas—some of which make it into our products.
Minimum Qualifications:
- Bachelor’s or advanced degree in Computer Science, Software Engineering, or a related field.
- A minimum of 10 years of full-time work experience as a software developer.
- Proficiency in technologies like: Apache Spark, Databricks, Kafka, SQL, Terraform.
- Strong programming experience in Python, Golang, Java, Scala, or another advanced object-oriented language.
- Hands-on experience with creating robust ETL pipelines.
- In-depth knowledge of data structures and algorithms.
- Skills in writing unit tests, data quality checks, and automated data testing frameworks.
- Proven backend development experience, including work on scalable, high-availability services.
- Excellent communication and interpersonal skills, with a track record of effective collaboration across cross-functional teams.
Additional Skills:
- Experience with AWS technologies.
- Practical experience with Kubernetes for orchestration and containerization.
- Proficiency in designing, implementing, and optimizing data models for data warehouses, databases, and data lakes.
- Familiarity with data warehousing concepts and platforms like Databricks, Iceberg, Snowflake, Amazon Redshift, or Google BigQuery.
- Experience with Schema Registries and Data Catalogs e.g. AWS Glue, Unity Catalog
- Experience with real time processing systems like Apache Kafka Streams and Kinesis.
- Experience with monitoring tools like Prometheus, Grafana, or cloud-native monitoring solutions and skills in optimizing performance for large-scale data processing.
Additional Qualities We Value:
- Demonstrated leadership experience in projects, even if not reflected by a formal title.
- A diverse knowledge base that facilitates solving complex technical challenges.
- Comprehensive understanding of software development practices, including expertise in writing and debugging code.
- Willingness to engage in our robust onboarding and on-the-job training programs.
Interview Process:
- Phone Technical Screening: Includes a brief coding exercise (approximately 30 minutes).
- Face-to-Face Interviews: Multiple team members will conduct 2-3 interviews to understand your background, potential role, and career goals. Be prepared to collaborate on a technical problem and discuss past projects.
Security Requirements:
- Adhere to Arctic Wolf’s Information Security policies, standards, processes, and controls to protect the confidentiality, integrity, and availability of Arctic Wolf business information assets.
- Employment is contingent upon passing a criminal background check and employment verification.
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