Analytics Engineer
WFA Digital Insight
The demand for specialized analytics engineers is skyrocketing, with a 25% increase in job postings over the past year. Plaid, a leader in financial technology, is seeking an experienced Analytics Engineer to drive GTM analytics and data science initiatives. With a strong foundation in SQL, dbt, and cloud warehouses, you'll thrive in this role. As the financial sector continues to evolve, Plaid's innovative approach to fintech has positioned the company for significant growth. Before applying, consider the company's emphasis on collaboration, data-driven decision making, and technical expertise.
Job Description
About the Role
The Analytics Engineer position at Plaid is a unique opportunity to drive business growth through data-driven decision making. As a key member of the Analytics Engineering team, you will be responsible for building and maintaining the core semantic layer data models, activation layer, and BI surfaces that support Plaid's GTM, CGX, NEA, and Marketing organizations. Your expertise in SQL, dbt, and cloud warehouses will enable you to partner with stakeholders to turn data models into actionable insights.The Analytics Engineering team is a critical component of Plaid's success, providing the foundation for data-driven decision making across the organization. As an Analytics Engineer, you will work closely with cross-functional teams, including Marketing, Sales, and Product, to drive business outcomes through data analysis and insights.
What You Will Do
- Own the dbt models and data marts that power Marketing analytics, activation, and reporting
- Build, validate, and productionize predictive models (lead scoring, LTV, channel attribution, propensity) in partnership with Marketing and GTM stakeholders
- Partner with Marketing leadership on measurement frameworks, experiment design, and spend optimization — translating business questions into analytical answers
- Enable self-serve analytics through AI tools and well-documented semantic models
- Collaborate with ML, Data Engineering, and Ops teams to deliver best-in-class data infrastructure to Marketing
- Develop and maintain data visualizations and BI surfaces to support business decision making
- Work closely with stakeholders to identify and prioritize analytics projects
- Develop and maintain technical documentation for data models, pipelines, and tools
- Stay up-to-date with industry trends and emerging technologies in analytics and data science
What We Are Looking For
- Bachelor's degree in a quantitative field (CS, Statistics, Economics, Engineering, or equivalent experience)
- 4+ years of proven experience in analytics engineering, data science, or a closely adjacent function
- Advanced SQL and production-grade data modeling experience — dbt strongly preferred
- Python proficiency for modeling and analysis work
- Hands-on experience with a modern cloud warehouse (Databricks, Snowflake, BigQuery, or Redshift)
- Demonstrated experience shipping predictive models or applied machine learning solutions
- Strong understanding of data architecture and data governance principles
- Excellent communication and collaboration skills
Nice to Have
- Experience with AI and machine learning technologies
- Knowledge of data engineering principles and practices
- Familiarity with Agile development methodologies
- Experience working with cross-functional teams
Benefits and Perks
- Competitive salary and equity package
- Comprehensive health, dental, and vision insurance
- Flexible PTO and remote work options
- Professional development opportunities
- Access to cutting-edge technologies and tools
- Collaborative and dynamic work environment
- Recognition and rewards for outstanding performance
- Opportunities for career growth and advancement
How to Stand Out
- Develop a strong portfolio showcasing your experience with SQL, dbt, and cloud warehouses.
- Highlight your ability to communicate complex technical concepts to non-technical stakeholders.
- Be prepared to discuss your experience with predictive modeling and machine learning.
- Show a willingness to learn and adapt to new technologies and tools.
- Research Plaid's company culture and values to demonstrate your alignment with the organization.
- Prepare examples of how you've driven business outcomes through data-driven decision making.
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