Senior Data Engineer, Data Platform

Alloy is where you belong!

Alloy solves the identity risk problem for companies that offer financial products by enabling them to outpace fraud and confidently serve more people around the world. Banks and fintechs turn to Alloy to take control of fraud, credit, and compliance risk, and grow with the clearest picture of their customers.

Through our values: Be Bold, Get Scrappy, Collaborate, and Celebrate Our Differences, we are creating a workplace where you can grow, thrive, and belong. See how we’ve been continuously recognized and named one of Inc.Magazine’s Best Workplaces, Forbes America’s Best Startup Employers, Best Fintech to Work for by American Banker, year after year. 

Check out our investors and read more about us here. 

About the team

We are seeking an experienced Senior Data Engineer to facilitate data usage and analytics at scale in Alloy. This role involves shaping the data engineering function and leading the consolidation, and delivery of data pipelines to serve the growing needs of Alloy’s platform data for internal and external users. If you have a passion for data, replication, and delivering high-quality reliable platforms, we’d love to hear from you.

This role will report to the Director of Engineering, and partner closely with the CTO as well as product and engineering leaders to refine and execute the technical vision for our data infrastructure. You’ll own and ensure the platform scales seamlessly with usage, integrates across different data connectors, and meets the highest standards of quality, availability, and governance.

What you'll be doing

As the Senior Data Engineer, your high-level responsibilities will be:

• Building a unified data platform to support real-time decision-making, analytics, reporting, and operational workflows.
• Transforming and streamlining data pipelines across the business to ensure consistent and reliable data availability across multiple teams and products.
• Developing the foundational data layer product and third party data integrations, to support external and internal clients. 

Your day-to-day will include:

• Designing and unifying highly scalable, robust, and secure data infrastructure using AWS, with familiarity in ETL/ELT such as DMS/Fivetran and data stores like Snowflake / Redshift.
• Partnering with cross-functional teams to identify and prioritize data availability needs, ensuring alignment with business goals. 
• Streamlining data processing, storage and costs, and delivery for internal and external use cases. 
• Troubleshooting and documenting critical issues in data pipelines and infrastructure.
• Hiring, mentoring and providing technical leadership engineers, and other technical stakeholders across the organization. 
• Leading initiatives to standardize governance around data security, compliance, and monitoring.
• Defining success metrics and KPIs to evaluate data platform performance and identify improvement areas. 

Who we’re looking for

We are looking for a proven data engineering leader first-in-seat with the expertise to establish and elevate Alloy’s data infrastructure. This role requires both a strategic mindset and hands-on technical proficiency to lead critical initiatives for the business. 

• 6+ years of engineering experience with a strong focus on building and migrating data pipelines or similar roles. 
• 3+ years of experience in a senior/staff-level role driving company objectives.
• Proficiency in SQL, Python, or similar languages for data manipulation and processing.
• Experience with building and scaling ETL/ELT pipelines and workflows using Airflow, dbt, or similar tools.
• Strong understanding of data warehouses like Redshift and Snowflake, and real-time data replication using tools like DMS or Fivetran.
• Experience building data delivery dashboards through Looker, Hex or similar products. 
• Advanced knowledge of AWS services, including S3, DynamoDB, Lambda, EC2, and RDS, with a strong focus on cost-efficient scaling. 
• Understanding of data security, and compliance best practices. 
• Worked with product and data scientist teams to design solutions that meet various operational and analytical needs. 
• Proven leadership in mentoring and developing engineers.
• Excellent written and verbal communication skills, with the ability to translate complex technical details into actionable insights for clients and internal teams.