CrowdStrike is a global leader in cybersecurity, dedicated to stopping breaches through advanced AI-native platforms. The role involves architecting and building data frameworks to support operational data stores and enterprise data lakes, collaborating with stakeholders to create scalable data solutions.
Responsibilities:
- Lead the full lifecycle of data engineering projects, from initial requirement gathering with stakeholders to production deployment and monitoring
- Design, develop and maintain complex data transformations, ensuring high data quality and performance using scripting languages like Python, Airflow, DBT and databases such as Snowflake or similar Data Lakes
- Build, scale, and maintain automated workflows using Apache Airflow to manage sophisticated data dependencies
- Maintain high engineering standards through CI/CD implementation and rigorous version control using GitHub
- Implement automated processes for data validation, ensuring high standards of data quality, accuracy, and integrity across all pipelines
- Act as a technical partner to the Analytics, Sales, and Marketing teams, building curated datasets that drive strategic decision-making
Requirements:
- 5+ years' experience in design & developing complex automation frameworks, queries, data modeling in SQL, Python, DBT, Apache Airflow
- Deep Experience in scripting languages such as Python and Cloud database experience such as Snowflake, Redshift, etc. to facilitate rapid ingestion and dissemination of key data
- Sales Data Domain Expertise: Hands-on experience working with Sales Pipelines and bookings (Accounts, Opportunity, Role hierarchy, etc), Quota Attainment, RBACs, etc
- Expertise in architecting scalable DBT projects using advanced modeling techniques, custom macros, complex Jinja-templated logic, and modular project structures to enforce DRY (Don't Repeat Yourself) principles across the enterprise
- Advanced proficiency in the DBT lifecycle including CI/CD processes such as Jenkins, Gitlab CI/CD etc., and source control tools such as GitHub, etc
- Experience identifying and solving issues concerning data management to improve data quality, and clean, prepare and optimize data for ingestion and consumption
- Proven experience integrating and managing business data from enterprise applications into Semantic Layers to decouple complex logic from the BI layer to drive analytics and insights
- Bachelor's Degree in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- Sales Automation Tools Knowledge: Experience with platforms such as Salesforce, People.ai, Clari and CRM systems for data integration and processing
- Understanding of machine learning concepts: Ability to collaborate with data science teams and support machine learning initiatives through data preparation, transformation and Feature store support