1 день назад
Senior Director, Data Engineering (AI Data Platform)
182 300 - 291 500$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Director, Data Engineering (AI Data Platform): Leading the architecture, development, and optimization of an enterprise data platform built on Snowflake, dbt, Dagster, DataHub, and adjacent AI infrastructure with an accent on governance, real-time operations, and AI-native engineering. Focus on building agentic development practices, supporting feature stores and RAG pipelines, managing platform FinOps, and leading federated data engineering teams.
Location: Newton Office, United States
Salary: $182,300–$291,500 per year
Company
is a Fortune 500 energy company operating across terminals, retail convenience stores, fuel marketing, and supply and trading.
What you will do
- Define and execute the enterprise data platform strategy and multi-year roadmap across Snowflake, dbt, Dagster, DataHub, Tableau, and adjacent ML/AI infrastructure.
- Lead the architecture and modernization of governed, reliable, cost-aware data systems, including streaming and near-real-time capabilities.
- Operationalize agentic development with Claude Code, Cursor, MCP-based tooling, AI-assisted code review, automated lineage, and agentic data quality workflows.
- Partner with Data Science/ML to provide feature stores, vector stores, RAG retrieval infrastructure, evaluation tooling, and model and agent observability.
- Lead data governance, data contracts, SLAs, MDM, lineage, security, privacy, compliance, and platform FinOps.
- Grow the central Data Engineering function, mentor technical leaders, and partner with analytics, product, IT, cybersecurity, and business units.
Requirements
- 12+ years of experience in data engineering, analytics engineering, or data platform leadership, including 7+ years in senior management and experience managing managers.
- Expertise with Snowflake, dbt, Dagster or Airflow, cloud lakehouse patterns, and production data systems with contracts, SLAs, lineage, and observability.
- Experience with cloud infrastructure, AWS, infrastructure as code, containerization, CI/CD, streaming architectures, and data platform FinOps.
- Demonstrated experience integrating AI-assisted and agentic development tools and governing LLM- and agent-based production features.
- Proficiency in Python and SQL, with working knowledge of feature stores, vector databases, RAG pipelines, embeddings, ML fundamentals, and BI tools.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or another quantitative field, plus experience in a federated data organization.
Culture & Benefits
- Medical, dental, vision, and life insurance with additional wellness support.
- 401(k) plan with company matching.
- Training, talent development, growth opportunities, and tuition reimbursement after six months of service.
- Inclusive workplace with equal employment opportunity commitments.
Hiring process
- Talent Acquisition reviews applications and may connect qualified candidates with the hiring manager.
- Interviews may be conducted virtually and in person, depending on the role.
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