Senior Software Engineer - Data Infrastructure
WFA Digital Insight
As demand for data-driven financial solutions surges, companies like Plaid are at the forefront. With a growth rate of 25% in fintech, skilled professionals are in high demand. This Senior Software Engineer role stands out for its focus on scaling data systems and enabling product innovation, making it an exciting opportunity for those with a passion for data infrastructure and machine learning. Before applying, candidates should be aware of the technical requirements and the company's dedication to making data-driven decisions.
Job Description
About the Role
The Senior Software Engineer - Data Infrastructure at Plaid is a crucial role in driving the company's mission to empower a healthier financial life for millions. This position involves leading key data infrastructure projects, working closely with stakeholders across various teams, and contributing to the long-term technical roadmap for data-driven iteration. As a domain expert in Data Warehouse, Data Lakehouse, Spark, Workflow Orchestration, and Streaming technologies, the successful candidate will play a pivotal role in scaling existing data pipelines while creating abstractions for seamless development.The data infrastructure team at Plaid is responsible for building the tools and experiences that thousands of developers use to create their own products. With Plaid's network covering 12,000 financial institutions across the US, Canada, UK, and Europe, the impact of this role is significant. The company is dedicated to making data-driven decisions, and this position is central to that effort.
What You Will Do
- Contribute towards the long-term technical roadmap for data-driven and machine learning iteration at Plaid
- Lead key data infrastructure projects such as improving ML development golden paths
- Implement offline streaming solutions for data freshness
- Build net new ETL pipeline infrastructure
- Evolve data warehouse or data lakehouse capabilities
- Work with stakeholders in other teams and functions to define technical roadmaps for key backend systems and abstractions across Plaid
- Debug, troubleshoot, and reduce operational burden for the Data Platform
- Grow the team via mentorship and leadership
- Review technical documents and code changes
What We Are Looking For
- 5+ years of software engineering experience
- Extensive hands-on software engineering experience with a strong track record of delivering successful projects within the Data Infrastructure or Platform domain
- Deep understanding of one of: ML Infrastructure systems or Data Infrastructure systems
- Strong cross-functional collaboration, communication, and project management skills
- Proficiency in coding, testing, and system design
- Demonstrated leadership and mentorship abilities
- Experience with Data Warehouse, Data Lakehouse, Apache Spark, Streaming Infrastructure, and Workflow Orchestration
Nice to Have
- Experience with feature stores, training infrastructure, serving infrastructure, and model monitoring
- Knowledge of cloud computing platforms such as AWS or GCP
- Familiarity with agile development methodologies
- Certification in data engineering or a related field
Benefits and Perks
- Competitive salary
- Equity in a leading fintech company
- Comprehensive health insurance
- Generous PTO policy
- Remote work stipend
- Professional development opportunities
- Access to cutting-edge technologies and tools
- Collaborative and dynamic work environment
How to Stand Out
- Ensure you have a deep understanding of data infrastructure systems, including Data Warehouses and Data Lakehouses, to stand out in the application process.
- Showcase your experience with Spark, Streaming Infrastructure, and Workflow Orchestration in your portfolio or resume.
- Be prepared to discuss your approach to scaling data pipelines and creating abstractions for other engineers.
- Highlight your proficiency in coding, testing, and system design, and be ready to provide examples of successful projects.
- Demonstrate your ability to work collaboratively and communicate effectively across different teams and functions.
- Consider highlighting any experience with machine learning infrastructure systems for an additional competitive edge.
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