Sr. Data Pipeline Engineer
WFA Digital Insight
The demand for skilled data pipeline engineers has skyrocketed in recent years, with a 25% increase in job postings in the last year alone. As companies continue to rely on data-driven insights to drive their business decisions, the need for professionals who can design, build, and optimize data pipelines has never been more pressing. Crowdstrike, a leader in the cybersecurity industry, is seeking an experienced Senior Data Pipeline Engineer to join their team. With the company's commitment to innovation and customer satisfaction, this role offers a unique opportunity for candidates to work on complex data pipelines and contribute to the company's mission. Before applying, candidates should be aware that this role requires strong technical expertise, excellent communication skills, and the ability to work in a fast-paced environment.
Job Description
About the Role
As a Senior Data Pipeline Engineer at Crowdstike, you will be responsible for designing, building, and optimizing large-scale data ingestion and processing pipelines. This is a critical role that will enable analytics and AI-driven insights, and ensure the scalability and reliability of the company's enterprise data platform. You will be working closely with a global team of data engineers, fostering coordination across time zones and driving operational excellence.The ideal candidate will have deep technical expertise, strong people leadership skills, and a proven ability to operate in a high-growth, fast-paced SaaS environment. You will be responsible for integrating a variety of data sources, including Salesforce, NetSuite, and Workday, and ensuring the quality, observability, and reliability of the data pipelines.
Crowdstike is a mission-driven company that values innovation, customer satisfaction, and community involvement. As a Senior Data Pipeline Engineer, you will be part of a team that is passionate about stopping breaches and protecting the people, processes, and technologies that drive modern organizations.
What You Will Do
- Collaborate with a global team of data engineers to design, build, and optimize large-scale data ingestion and processing pipelines
- Architect and oversee large-scale data ingestion and transformation pipelines using Airflow, DBT, Python, Kafka streaming, and Snowflake
- Design and implement real-time and batch ingestion frameworks integrating data from various business systems and APIs
- Manage data integration and transformation from enterprise systems such as Salesforce, NetSuite, Workday, and other core business applications
- Drive data quality, observability, and reliability across pipelines through monitoring, alerting, and proactive issue resolution
- Collaborate with data science and product teams to support AI assistance bot integration, AI/ML workflows, and product telemetry analytics
- Ensure engineering excellence by aligning data practices with DevOps principles, CI/CD automation, and robust data governance standards
- Oversee multiple projects simultaneously, managing priorities, and delivery timelines in a dynamic, high-velocity environment
- Communicate effectively with business and technical stakeholders to align data engineering initiatives with strategic organizational goals
What We Are Looking For
- 12+ years of experience in designing and building scalable data pipelines
- Demonstrated success working with distributed analytics and BI teams across multiple time zones
- Proven expertise with Airflow, DBT, Python, Kafka streaming, and Snowflake, including proficiency in advanced SQL for complex transformations and performance tuning
- Deep experience in API and file-based data ingestion, real-time streaming, and data pipeline orchestration at scale
- Hands-on experience with data integration from Salesforce, NetSuite, Workday, and similar business platforms
- Exposure to AI assistance bot integrations, data science workflows, and ML data pipelines
- Understanding of SaaS product telemetry, metadata management, and data governance principles
- Experience applying DevOps and CI/CD practices to data engineering environments
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field
Nice to Have
- Experience working for a SaaS security company and building business metrics
- Knowledge of cloud-based data platforms such as AWS or Google Cloud
- Familiarity with agile development methodologies and version control systems such as Git
- Certification in data engineering or a related field
Benefits and Perks
- 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 career growth
- Remote work options and flexible working hours
- Access to cutting-edge technologies and tools
- Collaborative and dynamic work environment
How to Stand Out
- To stand out as a candidate, be prepared to showcase your experience with scalable data pipelines and your ability to work with distributed teams.
- Make sure to highlight your expertise in Airflow, DBT, Python, Kafka streaming, and Snowflake, as well as your proficiency in advanced SQL.
- When applying, tailor your resume and cover letter to the specific requirements of the role, and be prepared to provide examples of your experience with data pipeline design, development, and optimization.
- During the interview process, be prepared to discuss your experience with data governance, security, and compliance, as well as your ability to communicate technical concepts to non-technical stakeholders.
- When negotiating salary, be sure to research the market rate for the role and be prepared to discuss your expectations and requirements.
- Be wary of companies that do not provide clear information about the role, team, or company culture, and be sure to ask plenty of questions during the interview process to ensure you have a clear understanding of the opportunity.
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