Director - Data Engineering

Waylin Partners, LLC

About The Position

Waylin Partners, a leading provider of FP&A, data, and accounting consulting services, is seeking a Data Engineer who is passionate about building scalable data solutions and solving complex technical problems. In this role, you will work directly with experienced finance and analytics professionals to design and deploy data infrastructure that enables faster, more accurate decision-making across our clients’ portfolio companies. You will lead data engineering initiatives that modernize reporting, automate key processes, and unlock insights through reliable, well-structured data systems.

Requirements

  • Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Analytics, or a quantitative field
  • 8+ years of experience in data engineering, analytics engineering, or related roles
  • Strong SQL proficiency and experience building ETL/ELT pipelines
  • Experience with cloud data platforms (Snowflake, Redshift, BigQuery, Azure Synapse, etc.)
  • Experience with BI tools such as Power BI, Tableau, Looker, or similar
  • Excellent communication skills with the ability to work directly with stakeholders and translate technical concepts into business impact

Nice To Haves

  • Proficiency in Python or another scripting language is a plus
  • Experience working with finance, accounting, or operational data strongly preferred

Responsibilities

  • Design, build, and optimize data warehouses, pipelines, and ETL/ELT processes to support enterprise reporting and analytics
  • Translate ambiguous business questions into scalable, data-driven solutions that help leaders make informed decisions
  • Develop automated reporting and analytics workflows, ensuring data accuracy, consistency, and timeliness
  • Build and maintain dashboards and visualization tools that synthesize complex data for finance and operational leadership
  • Partner with finance, accounting, and operational teams across portfolio companies to understand data needs and implement effective solutions
  • Implement best practices for data governance, data quality, and system architecture
  • Support integration efforts during acquisitions, system migrations, and new tool onboarding
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