Data Engineer, Sales Data Domain (Remote)

About the position As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations.

Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform.

Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We’re also a mission-driven company.

We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers.

We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters?

The future of cybersecurity starts with you. About the Role: We are seeking a seasoned Data Engineer to join our team. You will be responsible for architecting and building robust data frameworks that empower Operational Data Store / Enterprise Data Lake Platforms.

This role requires a blend of high-level technical expertise in modern data stacks and the ability to collaborate independently with stakeholders to translate business needs into 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. • You will work with your Data Engineering teammates to review design, code, and test plans to increase knowledge and application of key frameworks and methodologies. • Work with internal and external stakeholders to assist with data-related technical issues and support data infrastructure needs. • 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.

Nice-to-haves • 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.

Benefits • Market leader in compensation and equity awards • Comprehensive physical and mental wellness programs • Competitive vacation and holidays for recharge • Paid parental and adoption leaves • Professional development opportunities for all employees regardless of level or role • Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections • Vibrant office culture with world class amenities • Great Place to Work Certified™ across the globe