Director, Data Engineering & Analytics

The Director of Data Engineering & Analytics will be responsible for leading the execution of a strategic plan designed to enable O’Reilly to leverage data as a strategic, governed asset. The Director owns the data engineering, business intelligence, enterprise data warehousing, and analytics for the enterprise and works closely with all business areas to deliver a range of data and analytical solutions. This role will formulate and implement key technology and architecture decisions across the data platform ecosystem, foster and establish a strong engineering discipline, hire, develop, and build a strong engineering organization. The Director will work cross functionally on a day-to-day basis, manage a diverse team, focus on execution and possess strong problem solving and communication skills.

ESSENTIAL JOB FUNCTIONS

1. Provide strong leadership, vision and drive the implementation and development of the organization's data platform, data management, and analytics initiatives.
2. Demonstrate excellent knowledge of data warehouse principles, analytics, and reporting. Be an expert in data engineering, including building cloud data warehouse platforms (e.g., Snowflake, BigQuery), data marts, data science, and data pipelines.
3. Build and lead high-performing teams. Recruit, develop, and retain top talent in data engineering and analytics globally. Encourage teamwork and knowledge sharing within the team, across departments and countries.
4. Build a culture of engineering best practices, emphasizing data engineering standards, guidelines, and processes, data quality, documentation, data governance, service level objectives, and data contracts.
5. Establish and promote operational excellence through code reviews, documentation, CI/CD pipelines, monitoring, code quality, reusability, and maintainability. Build and maintain a robust data engineering toolchain.
6. Prioritize and manage projects, deliver data solutions on time and within budget, balancing competing priorities.
7. Foster a data-driven culture, promote data literacy and analytics throughout the organization, encouraging data-informed decision-making.
8. Create a comprehensive business intelligence and analytics strategy aligned with business goals.
9. Establish standardized Business Intelligence Center of Excellence model, development and deployment process. Empower business users with self-service BI capabilities and governance model.
10. Design and implement scalable data infrastructure to support international operations. Implement data localization strategies to meet specific country requirements and local data privacy regulations.
11. Provide technical guidance and mentorship to the data engineering and analytics team. Resolve complex technical challenges and make informed architectural decisions.
12. Influence and build strong partnerships with business leaders to drive data-driven decision making. Clearly articulate complex technical concepts to both technical and non-technical audiences.
13. Develop change management plans to drive adoption of new data solutions. Provide training and support to empower users to leverage data effectively.
14. Establish data observability practices to ensure data reliability and performance. Define and track key metrics to measure data quality and pipeline health.
15. Develop data storytelling and visualization capabilities to communicate insights effectively.
16. Implement data governance framework to manage data access, lineage, and compliance.
17. Protect data assets from unauthorized access or disclosure. Implement robust security measures, including encryption, access controls, and network security.
18. Ensure compliance with relevant data privacy regulations.
19. Optimize data storage, processing and consumption costs while maintaining data accessibility and performance.
20. Manage budgets and resources, optimize resource allocation to achieve business objectives.
21. Supervise and train staff, including organizing, prioritizing, and scheduling work assignments.
22. All other duties as assigned.

SKILLS/EDUCATION/KNOWLEDGE/EXPERIENCE/ABILITIES

Required:

1. Bachelor’s Degree in Computer Science, Information Technology, or Engineering.
2. 10+ years of experience in data warehouse, data migration, data engineering and analytics field.
3. 6+ years of successful data engineering, or analytics team management experience, including hiring, team member development, performance management, and delivering results.
4. 5+ years managing a team of data analysts/engineers/scientists.
5. 3+ years managing a team of architect/principal/staff/lead level team members.
6. Demonstrate a deep understanding of SQL and related databases.
7. Deep knowledge of designing and building highly scalable data warehouses, data pipelines, data modeling, designing data lakes and big data analytics.
8. Experience creating and delivering multi-quarter roadmaps. Demonstrated ability to deliver results in a fast-paced environment.
9. Prior experience with cloud data warehouse, data streaming platforms and dimensional models.
10. Experience with data ingestion, transformation, orchestration tools like FiveTran, Dbt, AirFlow.
11. Experience with data catalog, governance, quality and observability tools like Alation, Collibra.
12. Strong understanding of data architecture and design principles.
13. Experience in driving change/transformation through a larger operations focused organization.
14. Experience using Python, Java, or Spark for data processing.
15. Experience working with stakeholders and leaders to define and measure KPIs, service level objectives and other operating metrics.
16. Experience with data visualization and BI tools like Tableau, Looker, Domo.
17. Communication and leadership experience, with experience initiating and driving projects.
18. Proven ability to lead and manage high-performing teams. Strategic thinking and problem-solving abilities.
19. Strong collaboration skills in order to partner effectively across various levels of the organization.
20. Proven track record of successful communication of analytical outcomes through written communication, including an ability to effectively communicate with both business & tech teams.

Desired:

1. Advanced degree in Computer Science, Information Technology, or related field preferred.
2. Domain experience in retail and experience in the auto parts industry.
3. Proven experience in data stewardship, data governance, or a related role.
4. Ability to clearly articulate vision, mission, and objectives, and adapt the narrative appropriate to the audience.
5. Experience with medallion architecture/data tiers.
6. Knowledge of advanced analytics and machine learning techniques.
7. Hands-on experience with GCP, AWS or Azure cloud platforms.
8. Strong knowledge of data protection regulations, compliance and data management policies.
9. Strong understanding of cloud architecture, cloud storage, compute and hybrid (on-prem and cloud) data pipelines.

Total Compensation Package:

• Competitive Wages & Paid Time Off
• Stock Purchase Plan & 401k with Employer Contributions Starting Day One
• Medical, Dental, & Vision Insurance with Optional Flexible Spending Account (FSA)
• Team Member Health/Wellbeing Programs
• Tuition Educational Assistance Programs
• Opportunities for Career Growth

O’Reilly Auto Parts is an equal opportunity employer. Hiring decisions are administered without regard to race, color, creed, religion, sex, pregnancy, sexual orientation, gender identity, age, national origin, ancestry, citizenship status, disability, veteran status, genetic information, or any other basis protected by applicable federal, state or local law.

Reasonable Accommodations: Qualified individuals with known disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and certain state or local laws.