Staff Data Engineer

1 Month ago • 8-8 Years • Data Analysis • $127,000 PA - $169,000 PA

Job Summary

Job Description

Self Financial is a growing FinTech company focused on increasing economic inclusion and financial resilience. They are seeking a Staff Data Engineer to provide technical leadership, mentor teammates, and collaborate cross-functionally to improve their product. This role involves organizing plans that drive outcomes and making a direct impact on the company's mission. The Staff Data Engineer will be responsible for ensuring data is a strategic asset by delivering timely, high-quality data to support internal Analytics, Machine Learning, and Business Intelligence organizations. Key responsibilities include leading data pipeline development, data modeling, and populating data schemas for business intelligence and data analysis.
Must have:
  • 8+ years of experience in database development
  • 8+ years designing complex Data Warehouse/Lake models
  • Proficient in managing Data ETL/ELT
  • Experience with columnar data structures
  • Familiarity with AWS data warehousing tools
  • Experience with Git, JIRA, Confluence
  • Familiarity with Apache Airflow and Python
  • Excellent communication skills
Good to have:
  • Willingness to embrace team leadership
  • Collaborating with Product Management
  • Architecture design and planning
  • Creating Physical and Logical Data Models
  • Maintaining data lifecycle and quality standards
Perks:
  • Company equity (Stock Options)
  • Performance-based bonuses
  • Generous employer-paid health, vision, and dental insurance
  • Flexible vacation policy
  • Educational assistance
  • Free gym membership
  • Casual dress code
  • Team building events
  • Remote work arrangements/flexible work schedule
  • Paid parental leave

Job Details

Self Financial is a venture-backed, high-growth FinTech company with a mission to increase economic inclusion and financial resilience by empowering people to build credit and build savings.

We're looking for people who share our passion and are driven to tackle challenges, find solutions and make the financial space better for the communities we serve.

Our team is passionate about challenging the status quo of the credit industry by providing people accessible tools to take control of their credit. Executing on our mission requires deep collaboration across our teams to ensure our products reach the people who can benefit from them the most, particularly the 100 million+ Americans who have no or low credit.

We celebrate diversity and are committed to creating an inclusive environment for all employees. To that end, we seek to recruit, develop and retain the most talented people from a diverse candidate pool.

About the Role:

As our Staff Data Engineer, you will be responsible for organizing plans that drive outcomes and making a direct impact on our mission. We want you to provide technical leadership to your teammates through coaching and mentorship, collaborate cross-functionally to implement impactful improvements to our product.

As part of the Self Financial Data Engineering Team, your role will be to ensure that data remains a strategic asset for Self Financial by delivering timely, high-quality, and purpose-built data to our team members. Our team supports Self Financial's internal Analytics, Machine Learning, and Business Intelligence organizations.

What you will do:

  • Operates as part of a cross functional product development team that includes Architecture, Infrastructure, and Product Management
  • Your primary focus will be on leading the data pipeline, modeling, and populating data schemas within Self Financial's Data Environment for use in business intelligence and data analysis activities.
  • Your day-to-day activities will include:
    • Collaborating closely with Product Management to translate Self Financial's strategic vision into actionable projects.
    • Architecture design, project analysis, work break down and planning.  
    • Creating Physical and Logical Data Models with large, complex data sets
    • Managing data pipeline, ETL/ELT processes using SQL and Python
    • Maintaining data lifecycle and quality standards

Who you are:

  • 8+ years of experience with database development, database integration, and data analytics tools
  • 8+ years of experience designing and implementing complex Data Warehouse and Data Lake data models (Kimball)
  • Willingness to embrace the responsibilities of team leadership and accountability for team results
  • Proficient in managing Data ETL/ELT with large data sets
  • Experience with columnar data structures such as Amazon RedShift
  • Familiarity with AWS data warehousing tools
  • Experience with common software engineering tools such as Git, JIRA, Confluence and similar platforms
  • Familiarity with Apache Airflow and Python
  • Excellent listening, interpersonal, written, and oral communication skills

Base salary range: $127,000-169,000 annually.  Individual pay is based on factors unique to each candidate, including skill set, experience, and other job-related reasons.

Benefits and Perks:

We have the compensation and benefits you expect. But there's one thing that Self Financial can offer that many companies cannot: we can positively change the world, while making a profit. We are a team of Builders, empowering our customers to build their dreams. We have a Do the Right Thing ethos in all that we do, and we hope you value that approach, too. 

Our perks include:

  • Company equity in the form of Stock Options
  • Performance-based bonuses
  • Generous employer-paid health, vision and dental insurance coverage
  • Flexible vacation policy
  • Educational assistance
  • Free gym membership
  • Casual dress code
  • Team building events and activities
  • Remote work arrangements/ flexible work schedule
  • Paid parental leave 

Self Financial requires all employees hired to successfully pass a background check.

We are an Equal Opportunity Employer.

At this time, we are only able to consider applicants who are U.S. Citizens or Green Card Holders for employment opportunities. We appreciate your understanding.

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Austin, Texas, United States (Remote)

Austin, Texas, United States (Remote)

Austin, Texas, United States (On-Site)

Austin, Texas, United States (Remote)

Austin, Texas, United States (Remote)

Austin, Texas, United States (Remote)

Austin, Texas, United States (Remote)

Austin, Texas, United States (Remote)

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