Director of Data Engineering

Role Description

We are seeking an experienced Director of Data Engineering responsible for the technical leadership, architecture, and delivery of the company’s data platform. This role oversees the ingestion, storage, transformation, and availability of data for analytics and reporting. The Director will manage a small team of data analysts and engineers and will work closely with an external implementation partner during the initial build-out of the data lake and data warehouse.

The role requires strong experience with AWS-based data architectures, infrastructure automation, and modern analytics platforms, as well as the ability to integrate with external data platforms and transition systems from vendor-led implementation to internal ownership.

• Define and maintain the architecture for the company’s data lake and data warehouse
• Own the technical direction and standards for data ingestion, transformation, and storage
• Ensure data quality, reliability, security, and governance across the data platform
• Manage, mentor, and develop a team of data analysts and data engineers
• Set technical expectations, development standards, and operational practices
• Review designs, implementations, and analytics deliverables
• Work with an external partner to design and implement the initial data infrastructure
• Oversee knowledge transfer and transition to internal ownership
• Collaborate with application engineering, DevOps, and business teams to align data solutions with organizational needs
• Design and manage data pipelines that ingest data from multiple internal and external data sources in various formats
• Integrate and consume data from external platforms, including Databricks-based systems
• Support analytics and reporting use cases through curated datasets and data models
• Enable self-service analytics and reporting using Amazon QuickSight
• Build and operate data infrastructure on AWS, including S3, Glue, Athena, and Redshift or PostgreSQL
• Implement and maintain infrastructure as code using AWS CloudFormation
• Ensure deployments, monitoring, and operational processes are automated and repeatable
• Support AI and machine learning initiatives through data preparation and feature engineering
• Evaluate future technologies and platforms, including Databricks, as potential components of the data ecosystem

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent experience
• 8+ years of relevant professional experience
• 3+ years of people leadership experience
• Strong experience in data engineering and data warehousing architecture
• Experience ingesting, transforming, and modeling data from multiple data sources and formats
• Hands-on experience with AWS data services (S3, Glue, Athena)
• Experience with data warehouses such as Amazon Redshift and/or PostgreSQL
• Experience implementing infrastructure as code using AWS CloudFormation
• Proficiency in SQL
• Experience leading technical teams
• Experience integrating with external data platforms or vendor-managed data systems (e.g., Databricks)
• Python for data processing, automation, or analytics
• Familiarity with .NET-based application environments
• Knowledge of AI/ML concepts and model development workflows
• Experience with CI/CD pipelines and cloud security best practices

Benefits

• A competitive salary
• Comprehensive benefits, including health, dental, and vision insurance
• 401(k) plan options
• Paid time off, sick time, and paid holidays
• A fully remote work environment with flexibility and autonomy
• The opportunity to grow with a dynamic, innovative team in a startup-like culture