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Lead Data Science Engineer

1 month ago

Remote, Oregon, United States Cybrary Full time

Who We Are

Cybrary is the world leader in developing, measuring, and improving the skills of every cybersecurity professional and business worldwide. We believe the key to closing the cybersecurity skills gap is to arm cyber professionals with the skills they need to continuously develop in their field. Our enterprise-grade platform and rapidly expanding catalog support multiple types of learning, and allow for a personalized training experience for each user on the platform. With over 3 million users, Cybrary is well-positioned to accelerate its leadership position in the marketplace.

At Cybrary we value teamwork, collaboration, and trust. We look for people who like to win, embody grit, operate with a growth mindset, who love to learn, and approach each challenge with an open mind. We welcome diverse perspectives, and those who demonstrate the passion needed to disrupt the online and cybersecurity training industry. Our culture is shaped by fearless communication, nitro cold brew energy, collaborative community, and an up-for-anything attitude.

Headquartered in College Park, MD, Cybrary has been recognized as one of Washington D.C.'s Best Places to Work by Forbes and the Washington Post, and made Deloitte's Technology #Fast500 as one of the fastest growing technology companies in North America.


Cybrary is seeking an experienced Data Engineering Lead to join our team and drive the development and maintenance of our data infrastructure, pipelines, and warehousing solutions. This role will be responsible for ensuring efficient and reliable data flow, enabling data-driven decision-making across the organization. Cybrary currently uses Looker and various models across the organization, democratizing data access throughout the company.

Responsibilities:

  1. Data Infrastructure Management:
  • Work with Operations to manage and optimize the cloud infrastructure (GCP) for data processing and storage.
  • Ensure high availability, scalability, and performance of the data infrastructure.
Data Ingestion and Pipelines:
  • Design and expand robust data ingestion pipelines to collect and process data from various sources (current pipelines mostly use Cloud Run).
  • Optimize data pipelines for performance, reliability, and maintainability.
Data Warehousing:
  • Manage and optimize the data warehouse solution (Snowflake) for efficient data storage and querying.
  • Manage and improve the data transformation process in Snowflake.
  • Ensure data quality, integrity, and governance within the data warehouse.
Team Leadership and Collaboration:
  • Lead the data team in improving data infrastructure, including the above systems, as well as semantic modeling (Looker) and machine learning models.
  • Collaborate with the data team, engineering, and other business stakeholders to understand core business needs and implement solutions.

Requirements:

  • Minimum of 5 years of experience in data engineering roles, with a strong background in cloud infrastructure management, data pipelines, and data warehousing.
  • Proficient in programming languages such as Python, Scala, or Java, and experience with data engineering tools like Apache Spark, Apache Kafka, and Airflow.
  • Expertise in cloud platforms such as AWS, GCP, or Azure.
  • Hands-on experience with data warehousing solutions like Snowflake, Redshift, or BigQuery.
  • Strong understanding of data modeling, ETL/ELT processes, and data quality assurance methodologies.
  • Excellent problem-solving, analytical, and communication skills.
  • Ability to work collaboratively in a cross-functional team environment.

Preferred Qualifications:

  • Experience in our core stack (Python, GCP, Cloud Run, Airflow, Snowflake, Looker).
  • Experience leading data engineering / data science teams.
  • Knowledge of DevOps practices and tools (Docker, Kubernetes, Terraform).
  • Familiarity with data governance, security, and compliance best practices.
  • Experience with streaming data processing and real-time data pipelines.

If you are a passionate data engineering professional with a strong technical background and leadership skills, we invite you to apply for this exciting opportunity. Join our team and play a crucial role in shaping and scaling our data infrastructure to drive business growth and success.
This position is 100% remote, however the candidate must currently live within the United States.


What We Bring to the Table

Eligible employees qualify for a competitive total rewards package inclusive of the following benefits:

  • Competitive salaries that align with market and industry standards
  • 100% coverage of medical, vision, and dental insurance premiums for employees
  • 50% premium coverage for dependents
  • Available HSA and FSA programs
  • Company-paid life insurance coverage
  • Company-paid short-term and long-term disability coverage
  • Flexible sick and vacation leave, with dedicated parent and bereavement leave policies
  • Birthday Leave
  • 401(k) plan
  • Company-paid student loan repayment after 6 months of service
  • Referral bonus plan
  • Professional Development and Training reimbursement package

Cybrary is proud to be an Equal Opportunity Employer, and does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, national origin, veteran status or any other basis covered by applicable law.

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