Data Engineer, Go to Market; Remote

Crowd Strike, Inc.

Full time

R28144

As a global leader in cybersecurity, Crowd Strike 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 Crowd Strike 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 Crowd Striker both the flexibility and autonomy to own their careers. We're always looking to add talented Crowd Strikers 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.

We are seeking a seasoned Data Engineer with expertise in Go To Market domain 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.

• 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 Git Hub.

• 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.

• 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 Git Hub, 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.

• 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…