Senior Staff Software Engineer, Backend (Data and Storage Services)
WFA Digital Insight
As the demand for skilled backend engineers continues to surge, with a 25% increase in remote job postings in the last year, Affirm's Senior Staff Software Engineer role stands out. With the company's focus on building a large-scale, highly-available infrastructure, this position requires a unique blend of technical expertise and leadership skills. Candidates should be well-versed in data analytics and storage solutions, with a keen eye for innovation and optimization. Before applying, it's essential to understand the company's commitment to operational excellence and technical design review. With the right skills and experience, this role offers a chance to make a significant impact in the fintech industry.
Job Description
About the Role
The Senior Staff Software Engineer will play a critical role in Affirm's engineering team, focusing on the development and maintenance of the company's data and storage services. As a key member of the Data and Storage Services team, you will collaborate with various stakeholders to design and implement scalable, high-performance analytical infrastructure. The team's mission is to provide trustworthy, intuitive, and cost-efficient solutions for Affirmers to secure, store, analyze, and transform data at exceptional scale.The successful candidate will have a deep understanding of backend engineering, data analytics, and storage solutions. They will be responsible for architecting and evolving Affirm's lakehouse analytics platform, driving strategy around Snowflake, Apache Iceberg, and Spark. The role requires a strong technical leader who can collaborate with cross-functional teams, including Product, Infrastructure, and Analytics Engineering.
What You Will Do
- Architect and evolve Affirm's lakehouse analytics platform, driving strategy around Snowflake, Apache Iceberg, and Spark to deliver scalable, high-performance analytical infrastructure.
- Design and implement robust Role-Based Access Control (RBAC) and dynamic data masking policies in Snowflake, ensuring data access is secure, compliant, and auditable across the organization.
- Lead the technical direction of analytics engineering practices, including data modeling, transformation pipelines (dbt), and data quality frameworks that enable trustworthy, self-service analytics.
- Drive data governance and privacy engineering initiatives, leveraging tools like Atlan to manage data cataloging, lineage, classification, and policy enforcement.
- Identify and execute cost optimization strategies across Affirm's analytical compute and storage footprint, including Snowflake warehouse tuning, query optimization, and efficient data lifecycle management.
- Collaborate with product engineering, data science, and business intelligence teams to understand their data needs and provide continuous guidance on design, architecture, and best practices.
- Establish and champion best practices for lakehouse operations at scale, including schema evolution, table maintenance, partitioning strategies, and observability.
- Stay ahead of industry trends in analytical data platforms, data governance, and privacy technologies, and identify opportunities to innovate and improve our data offerings.
- Mentor engineers across the Lake Analytics Platform and Analytics Engineering teams, providing guidance on emerging technologies, development practices, and fostering a culture of technical excellence.
- Participate in an on-call rotation and collaborate with other teams such as SRE to resolve production issues.
What We Are Looking For
- 8+ years of experience in software engineering, with a focus on backend development and data analytics.
- Strong technical leadership skills, with experience in architecting and implementing scalable, high-performance analytical infrastructure.
- Expertise in data storage and analytics solutions, including Snowflake, Apache Iceberg, and Spark.
- Experience with data governance and privacy engineering initiatives, including data cataloging, lineage, classification, and policy enforcement.
- Strong understanding of cloud-based infrastructure and data security.
- Excellent communication and collaboration skills, with experience working with cross-functional teams.
- Bachelor's degree in Computer Science, Engineering, or a related field.
Nice to Have
- Experience with dbt, data modeling, and transformation pipelines.
- Knowledge of Atlan and other data governance tools.
- Experience with cost optimization strategies and efficient data lifecycle management.
- Familiarity with industry trends in analytical data platforms, data governance, and privacy technologies.
Benefits and Perks
- Competitive salary and equity package.
- Comprehensive health, dental, and vision insurance.
- 401(k) matching program.
- Flexible PTO policy and remote work options.
- Professional development opportunities and conference sponsorships.
- Access to cutting-edge technologies and tools.
How to Stand Out
- Ensure you have a strong understanding of data analytics and storage solutions, including Snowflake, Apache Iceberg, and Spark.
- Highlight your technical leadership skills and experience in architecting and implementing scalable, high-performance analytical infrastructure.
- Be prepared to discuss your experience with data governance and privacy engineering initiatives, including data cataloging, lineage, classification, and policy enforcement.
- Showcase your ability to collaborate with cross-functional teams, including product engineering, data science, and business intelligence teams.
- Demonstrate your knowledge of industry trends in analytical data platforms, data governance, and privacy technologies.
- Prepare examples of your experience with cost optimization strategies and efficient data lifecycle management.
- Be ready to discuss your approach to mentoring engineers and fostering a culture of technical excellence.
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