Data Analyst 2
Abnormal Security
CloudPythonSQLTableau
Data Analyst II – Detection Efficacy
Abnormal Security
full-time
Posted on:
Origin: • 🇨🇦 Canada
Visit company websiteJob Level
Mid-LevelSenior
Tech Stack
CloudPythonSQLTableau
About the role
- Contribute to the design, development, and maintenance of the DBT analytics pipeline, ensuring accurate representation of system performance and enabling data-driven decision-making across the organization.
- Build scalable, well-structured datasets and develop innovative data models that enhance the accessibility and depth of our analytics capabilities.
- Define and formalize key metrics in collaboration with stakeholders, ensuring they are stable, effective, and aligned with strategic goals.
- Conduct regular audits of metrics across teams and organizational levels to maintain consistency, accuracy, and relevance.
- Analyze complex data to uncover actionable insights that support decision-making, experimentation, and continuous improvement within Detection.
- Partner closely with Detection leadership and team leads to drive adoption and effective use of metrics and analytical outputs.
- Continuously improve processes for metric definition, inspection, and reporting to maximize their impact and usability.
- Provide training and support to teams on interpreting metrics and using analytics tools effectively.
Requirements
- 3+ years of experience working with large-scale data in analytical or product-oriented environments, with a strong focus on data exploration, interpretation, and communication.
- Proficiency in writing complex SQL queries and building clean, reliable data models to support reporting and analysis.
- Hands-on experience using DBT (Data Build Tool) to transform and organize data for downstream analytics workflows.
- Strong grasp of data analyst best practices, including analysis reproducibility, validating results through testing and sanity checks, and communicating insights clearly to both technical and non-technical audiences.
- Experience with at least one programming language (e.g., Python or R) for data exploration, statistical analysis, and automating reporting workflows.
- Bachelor's degree in a quantitative field such as Data Science, Mathematics, Statistics, Computer Science, Information Systems, or a related discipline.
- Demonstrated ability to translate ambiguous business questions into structured analyses and data models optimized for insight generation.
- Strong track record of collaboration with cross-functional partners to deliver high-impact data solutions.
- MS degree in Data Science, Mathematics, Statistics, Computer Science, Information Systems or other related engineering field (Nice to have).
- Experience with predictive modeling or statistical analysis techniques to support deeper insights and forecasting (Nice to have).
- Proficiency with business intelligence tools (e.g., Looker, Tableau, Power BI) to build intuitive dashboards and communicate insights effectively (Nice to have).
- Exposure to cloud-based data platforms (e.g., Snowflake, Databricks) and modern data stack tools (Nice to have).
