Director of Technology, Enterprise Data Engineering
J
JobgetherEnterprise data engineering
Candidates must currently reside in the United States. The position is fully remote.Full-TimeDirector
Salary120,000 - 186,000 USD per year
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Job Details
- Experience
- At least 10 years of experience in data engineering or a related specialized technology field, including at least three years of team leadership or management experience.
- Required Skills
- SQLCI/CDData modelingDatabricksPySpark
Requirements
- At least 10 years of experience in data engineering or a related specialized technology field.
- At least three years of team leadership or management experience.
- A bachelor's degree in Computer Science, Information Systems, or a related discipline, or equivalent professional experience.
- Experience leading legacy-to-cloud data platform migrations, enterprise data integrations, vendor-provided SaaS solutions, and internally developed systems.
- Strong hands-on knowledge of Databricks, including Unity Catalog, Delta Lake, medallion architecture, and Databricks Asset Bundles or YAML-based configurations.
- Advanced SQL and PySpark skills, with experience working with large governed datasets.
- Understanding of dimensional modeling, semantic layers, domain-driven design, and data lifecycle management.
- Experience building certified datasets and semantic models for self-service analytics or AI-assisted natural-language querying.
- Familiarity with data quality frameworks, automated testing, reconciliation, historical data management, CI/CD, version control, and governed deployment environments.
- Practical experience using AI tools such as Claude, Copilot, ChatGPT, or Gemini; understanding of AI output validation, responsible AI, and AI governance.
- Experience designing or governing AI-assisted development workflows, including specification-driven development, autonomous coding agents, automated code review, and testing pipelines.
- Experience collaborating with Information Security and applying data privacy, access control, and regulatory requirements.
- Experience planning technical initiatives, managing resources and budgets, coordinating vendors, and owning technical decisions and delivery outcomes.
- Strong analytical, organizational, and problem-solving skills, including the ability to explain technical concepts to business stakeholders and influence senior leaders.
Responsibilities
- Lead, coach, and develop data engineering professionals, including performance management, staffing, workload distribution, and career development.
- Lead domain-by-domain migration of legacy data lakes and curated data stores to Databricks, resolving differences across development, testing, and production environments.
- Partner with Enterprise Architecture to turn strategic direction into production-ready pipelines, data models, platform designs, and engineering practices.
- Own data ingestion and bronze, silver, and gold medallion architecture standards while maintaining and expanding data pipelines and integrations.
- Develop and maintain the semantic data layer, Unity Catalog objects, and curated datasets with Enterprise Data and Analytics Operations.
- Establish reusable pipeline templates, scaffolding, reference architectures, and automated tooling for self-service engineering.
- Integrate AI tools and agentic development practices into code generation, testing, documentation, and automated reviews, and define standards for their use.
- Ensure engineering deliverables meet data quality, lineage, documentation, privacy, and regulatory requirements; collaborate with Information Security on audits and vulnerabilities.
- Manage system integration partners and platform vendors, and communicate progress, risks, dependencies, and recommendations to senior leaders and business stakeholders.
- Define and monitor service-level agreements, operational KPIs, platform costs, and data quality metrics; lead troubleshooting and maintain technical documentation and runbooks.
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