Director of Analytics Engineering, Current

• 10+ years of experience in Analytics Engineering, Data Engineering, or Data Architecture, with at least 5+ years in a leadership or management capacity
• Proven track record of building and scaling enterprise-grade Data Warehouses from the ground up. You have completed multiple full development lifecycles
• Deep mastery of Kimball/Star Schema methodologies and how to apply them to modern, high-velocity fintech data
• Expert-level SQL and performance tuning skills. Significant experience with dbt (preferred), BigQuery (or similar MPP like Snowflake), and orchestration tools like Airflow
• Intermediate to advanced level programming skills in Python or other languages
• Extensive experience building scalable data models and reporting layers in Looker (LookML) or similar enterprise BI tools
• You are comfortable toggling between strategic planning and a terminal window. You enjoy being "on the ground" with your team to solve complex problems
• You are passionate about mentorship and have experience defining roles, hiring top talent, and managing career growth in a fast-paced environment
• Strong experience with cloud ecosystems like GCP or AWS
• Ability to explain complex technical concepts to non-technical stakeholders (e.g., Credit, Finance, and Executive teams)

Desirable

• As the Director of Analytics Engineering, you will be the strategic architect and hands-on leader of Current’s data transformation layer
• You will lead the Analytics Engineering effort for BI and Analytics at Current, ensuring our data and analytics infrastructure is scalable, reliable, and deeply aligned with business goals
• This is a high-impact leadership role requiring a "player-coach" mentality. You will define the long-term vision for our data warehouse, oversee the execution of complex ETL/ELT pipelines, and serve as the primary bridge between technical engineering teams, analysts, product managers and business stakeholders
• Beyond the tech stack, you will be responsible for mentorship, organizational design, and defining the career paths for a high-performing team of analytics engineers
• Define and drive the Analytics Engineering and BI strategy. Own the roadmap and P&L for data warehousing, modeling, and business intelligence across the entire organization
• Act as an engineer leading by example when necessary i.e. optimizing complex SQL, reviewing design, dbt models, data models, and troubleshooting high-priority pipeline issues
• Lead the design and implementation of robust dimensional models, data marts, and aggregation layers in BigQuery using dbt and Airflow
• Collaborate with leaders and stakeholders in different departments to translate business requirements into high-fidelity data models that power Looker and downstream analytics
• Manage and grow a world-class Analytics Engineering team including an off-shore team. Define clear career ladders, conduct performance reviews, and foster a culture of technical excellence and data curiosity
• Establish frameworks for data reconciliation, quality management, and security. Ensure the organization has absolute confidence in the accuracy and integrity of our data assets
• Own the Business Intelligence tooling and frameworks
• Drive the adoption of data models, customer data platform, business intelligence tooling and reporting frameworks
• Collaborate with Data Platform Engineers and Infrastructure teams to implement and evaluate modern tooling for data ingestion, transformation, and observability, while also establishing robust data governance practices