Partner hand in hand with the Director of Data to translate platform and data strategy into engineering execution, operating as peers across the data organization.
Take an already high-performing data engineering team and keep it aligned with best practices — establishing, championing, and continuously reinforcing standards for modeling, transformation, testing, and documentation as the platform evolves.
Provide strategic direction and technical leadership to the data engineering team, defining and executing the data engineering roadmap in alignment with the broader business and data strategy.
Operate as a hands-on leader in a role split roughly 50% management / 50% individual contribution.
Define and maintain data architecture standards and best practices that ensure the consistency, reliability, and maintainability of data pipelines and systems.
Lead the design and implementation of data models and schemas that enable integration and analysis across the platform.
Architect and build complex data systems, including large-scale data migration projects.
Design, implement, and manage data pipelines, ETL processes, and data warehousing solutions for efficient ingestion, transformation, and storage.
Partner with the DevOps team to deploy new data prototypes and R&D initiatives.
Debug and optimize long-running queries, tuning pipelines for performance, scalability, and reliability across data volume, velocity, and variety.
Recruit, hire, onboard, and mentor a high-performing data engineering team — setting clear expectations, providing regular feedback, and conducting performance evaluations.
Foster a collaborative, inclusive team environment that promotes professional growth and skill development.
Evaluate and select technologies, tools, and platforms that enhance data engineering capability and scale.
Collaborate with data scientists, analysts, software engineers, and other stakeholders to translate data requirements into solutions that meet business needs.
Partner with IT, security, and compliance teams to maintain data privacy, security, and compliance standards.
Monitor and troubleshoot data engineering processes, resolving issues quickly.
Stay current with industry trends and emerging technologies, driving innovation and continuous improvement across processes, tools, and methodologies.
Requirements
8+ years of experience in data engineering or a related field, including 3+ years in a leadership/management role.
Bachelor's degree or higher in Computer Science, Data Science, Information Technology, or a related field. A master's degree is a plus.
Deep expertise in data pipeline design, ETL processes, data warehousing, and data integration.
Advanced proficiency in SQL and Python; familiarity with R is a plus.
Experience with cloud data platforms (AWS, Azure, GCP) and modern data warehouses (Redshift, BigQuery, Snowflake).
Solid command of database systems, data modeling, and schema design.
Proven ability to manage complex projects and deliver high-quality results on time.
Excellent leadership, communication, and interpersonal skills, with the ability to articulate technical decisions to both technical and non-technical stakeholders.
Strong analytical and problem-solving skills, with a focus on innovation and continuous improvement.
Other duties as assigned.
Tech Stack
Amazon Redshift
AWS
Azure
BigQuery
Cloud
ETL
Google Cloud Platform
Python
SQL
Benefits
Premier health, dental, and vision insurance plans
401K matching
Unlimited paid time off
Paid personal and volunteer leave
13 paid holidays
15 weeks paid parental leave
Professional development stipend & tuition reimbursement
Macbook Pro laptop & tech accessories
Bring Your Own Device (BYOD) stipend for mobile device
Employee Assistance Program (EAP)
Supportive & collaborative culture
Flexible working hours
Remote friendly (within the U.S.)
Pre-tax transportation options for commuting to our office in Washington, DC