Director, Data Engineering
J
JobgetherTechnology
Remote work flexibility within the United States or Canada.Full-TimeDirector
SalaryCompetitive compensation package with a base salary range of $200,000 - $230,000 plus a 15% bonus opportunity.
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Job Details
- Experience
- 8+ years of experience in data engineering, software engineering, or related technical disciplines, including 4+ years managing engineers.
- Required Skills
- PythonSQLSnowflakeAirflowData modelingdbtLLM
Requirements
- 8+ years of experience in data engineering, software engineering, or related technical disciplines.
- 4+ years managing engineers.
- Experience building and leading multidisciplinary data teams across areas such as data engineering, machine learning, analytics, or software engineering.
- Advanced proficiency in SQL and Python.
- Strong knowledge of data modeling, master data management, and data architecture principles.
- Hands-on experience with modern data platforms such as Snowflake and dbt.
- Experience with orchestration tools including Airflow, Dagster, or Prefect.
- Proven ability to define and implement AI and LLM enablement strategies, including experience building with AI tooling.
- Experience operating at a Director level, including ownership of budgets, roadmaps, technical strategy, and executive communication.
- Strong leadership, mentoring, collaboration, and communication skills.
Responsibilities
- Define and execute the long-term data strategy and architecture, ensuring scalable, reliable, and trusted data foundations.
- Design, build, maintain, and optimize high-impact data pipelines connecting business systems, internal platforms, and data warehouses.
- Establish engineering standards for pipeline development, data modeling, governance, quality, and operational excellence.
- Act as a hands-on technical leader by contributing directly to complex projects, resolving technical challenges, and guiding engineering decisions.
- Build, structure, and lead a multidisciplinary Data organization spanning Data Engineering, Machine Learning Engineering, and Analytics.
- Own team growth initiatives, including hiring plans, organizational design, budget planning, and talent development.
- Partner with executive and cross-functional leaders to translate business goals into data strategies, platform investments, and technical roadmaps.
- Evaluate existing integrations, automation processes, and data workflows to identify opportunities for improvement and modernization.
- Champion AI and automation initiatives by ensuring emerging technologies are supported by reliable, scalable data infrastructure.
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