Senior Manager, Data Engineering

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

📋 Description

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

• Engage directly in the creation of high-impact pipelines, perform code and architecture reviews, and address complex troubleshooting issues.

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

• Manage a team of 5–8 data engineers, including responsibilities for hiring, onboarding, performance evaluation, compensation recommendations, and employee retention.

• Offer coaching, constructive feedback, and career development strategies.

• Cultivate an inclusive and trustworthy team environment.

• Strategize, prioritize, and coordinate the data engineering portfolio of the team.

• Establish and enhance agile delivery methodologies, including intake processes, estimation, sprint planning, and retrospectives.

• Identify, communicate, and mitigate risks, obstacles, and cross-team dependencies.

• Ensure the operational health of the team's data products, including service level agreements (SLAs), on-call responsibilities, incident management, and post-incident reviews.

• Develop strong relationships with both business and technology stakeholders, translating objectives into prioritized data engineering results.

• Collaborate with architecture, data engineering, AI, governance, and product teams to deliver comprehensive data solutions.

• Articulate technical concepts, trade-offs, roadmaps, and progress to engineers and senior leadership.

• Contribute to shaping the data engineering strategy, standards, and execution across the organization.

⛳️ Requirements

• Extensive experience in data engineering.

• Hands-on proficiency with Databricks, including Spark, Lakeflow, Spark Declarative Pipelines (DLT), Delta Lake, Lakebase/Postgres, and Unity Catalog.

• Familiarity with the Azure data ecosystem.

• Proven experience in formally managing data engineers, encompassing hiring, performance management, and career development.

• Demonstrated success in delivering production-grade data platforms and pipelines at scale.

• Strong focus on reliability, security, and cost efficiency.

• Capability to lead intricate technical projects through influence rather than authority.

• Outstanding communication, stakeholder management, and prioritization abilities in a global, matrixed setting.

• Client-service oriented mindset.

• Knowledge of contemporary data architecture patterns, including Lakehouse, Unity Catalog, medallion, and data mesh.

• Understanding of DataOps practices.

• Awareness of metadata-driven and configuration-driven pipeline frameworks.

• Experience guiding teams through technological transitions and the adoption of new data tools.

• Familiarity with CI/CD and infrastructure-as-code tools, such as Azure DevOps, Databricks Automation Bundles (DABS), GitHub Actions, or similar.

• Experience in leading cross-team initiatives across various geographies and time zones.

• Ability to work within the US/EMEA time zone.

🏝️ Benefits

• Health insurance

• Vision insurance

• Dental insurance

• Flexible spending accounts

• Health savings accounts

• Retirement savings plans

• Life insurance

• Disability insurance

• Paid time away from work

• Unpaid time away from work

• Competitive pay

• Inclusive culture

• Career development planning and coaching