Manager, Data Engineering AI
New
J
JobgetherData engineering
Fully remote position within the United StatesFull-TimeManager
SalaryBase compensation range of $145,000–$175,000 USD; Eligibility for discretionary bonus consideration.
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Job Details
- Experience
- 7+ years of combined experience in data engineering, IT, or project management, including at least 2 years of people-management experience.
- Required Skills
- AWSETLHadoopSnowflakeData engineeringSparkDatabricksMLOpsLangChain
Requirements
- Bachelor’s degree or equivalent professional experience.
- 7+ years of combined experience in data engineering, IT, or project management.
- At least 2 years of people-management experience.
- At least 2 years of experience leading small to mid-sized projects using established project management methodologies, processes, and artifacts.
- 4+ years of experience with complex datasets and modern data engineering technologies such as Hadoop, Spark, Databricks, AWS technologies, Snowflake, or comparable data integration and ETL platforms.
- 2+ years of experience with AI engineering concepts and tools such as Retrieval-Augmented Generation (RAG), prompt engineering, LangChain, LangGraph, or similar technologies.
- Familiarity with MLOps and LLMOps capabilities and platforms, including DataRobot or comparable solutions.
- At least 2 years of hands-on experience in software development and database management.
- Proficiency with Microsoft Office Suite.
- Strong leadership, coaching, mentoring, conflict-resolution, and stakeholder-management capabilities.
- Experience with healthcare data, particularly in a data operations environment, is preferred.
- Experience working in Agile environments is preferred.
- Ability to work remotely with a dedicated, secure workspace and reliable high-speed internet connectivity.
Responsibilities
- Lead, coach, mentor, and develop the data engineering team, including performance management and professional development.
- Develop and implement data engineering architecture strategies aligned with business objectives and organizational priorities.
- Establish reusable templates, reference architectures, and engineering patterns for pipelines connecting on-premises and cloud data sources.
- Partner with Architecture, Product, Business Leads, and Functional Product Managers on data product strategy and data literacy.
- Monitor AI trends, technologies, and engineering practices and identify opportunities to improve productivity and data architecture.
- Lead strategic data engineering and IT projects using appropriate project management methodologies.
- Serve as a point of contact for internal stakeholders and clients, communicating technical concepts and strategic decisions.
- Make technology decisions and optimize service costs through effective use of internal teams, external resources, and development capabilities.
- Work with privacy and security stakeholders to support compliance with internal standards, regulatory requirements, and applicable legal obligations.
- Support and improve disaster recovery, emergency operations, backup, security, and access-control plans.
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