Director, Data Engineering Delivery

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and implement data engineering strategies, standards, and execution throughout the organization.

• Oversee the design, construction, and ongoing enhancement of scalable data pipelines, Lakehouse architectures, and data products utilizing Databricks and Azure.

• Actively participate in the creation of impactful data pipelines, conduct code reviews, architecture assessments, and tackle complex troubleshooting challenges.

• Advocate for data quality, observability, security, and governance practices.

• Directly supervise a team of 5–8 data engineers and analysts.

• Manage hiring, onboarding, performance evaluations, compensation suggestions, and employee retention.

• Offer coaching, constructive feedback, and guidance for career development.

• Cultivate an inclusive, trust-based team culture.

• Strategically plan, prioritize, and coordinate the team’s data engineering initiatives.

• Establish and improve agile delivery methodologies.

• Identify, relay, and address risks, obstacles, and cross-team dependencies.

• Ensure the health of production systems, focusing on SLAs, on-call responsibilities, incident response, and post-incident analysis.

• Build strong relationships with business and technology stakeholders, translating objectives into prioritized data engineering outcomes.

• Collaborate with the Global Data Leadership team on architecture, data engineering, AI, governance, and product strategies.

• Clearly convey technical concepts, trade-offs, project roadmaps, and progress updates to engineers and senior executives.

⛳️ Requirements

• Proficiency in Databricks and the Azure ecosystem.

• Flexibility to assess and integrate new data technologies as the platform develops.

• Proven experience in managing deliverables and workflows for a team of data engineers.

• Background in constructing data platforms and nurturing data engineering talent.

• Capability to lead, mentor, and develop a team of 5–8 data engineers and analysts.

• Hands-on expertise with data engineering tasks on Databricks and Azure.

• Experience with scalable data pipelines, Lakehouse architectures, and data products.

• Understanding of engineering and architectural standards related to performance, reliability, and cost efficiency.

• Familiarity with conducting code reviews, architecture evaluations, and complex troubleshooting.

• Knowledge of data quality standards, observability, security, and governance practices.

• Experience in hiring, onboarding, performance assessment, compensation recommendations, and retention strategies.

• Proven track record in providing coaching, feedback, and career development support.

• Experience in planning and managing a portfolio of data engineering projects.

• Understanding of agile delivery methods, including project intake, estimation, sprint planning, and retrospectives.

• Experience with risk management, addressing blockers, dependency resolution, SLA management, incident response, and post-incident reviews.

• Ability to forge relationships with business and technology stakeholders.

• Proficiency in articulating technical concepts, trade-offs, project roadmaps, and progress to engineers and senior executives.

🏝️ Benefits

• Health insurance

• Vision insurance

• Dental insurance

• Flexible spending accounts

• Health savings accounts

• Retirement savings plans

• Life insurance

• Disability insurance programs

• Paid and unpaid time off

• Competitive salary