From Student Projects to Senior Engineer: Nathan Fritter's Success Story at Capital One

From Student Projects to Senior Engineer: Nathan Fritter's Success Story at Capital One

Introduction

Landing a job in data science can be tough. Many job seekers struggle with endless applications and few responses. If you’re feeling stuck in your job search, you’re not alone.

Nathan Fritter, now a senior data engineer at Capital One, shares effective strategies for using platforms like hired.com, networking with recruiters, and starting a career in data science. His tips can help you stand out and succeed in this competitive field.

Can you tell us how you got into data science?

Sure, I’d be happy to share how I got into the data science space. If you look at my profile, you’ll see that my involvement in the data science club at UCSB was a major turning point.

It all started quite casually. I was in between majors at the time, considering fields like actuarial science. My college roommate mentioned this data science club, saying it was an up-and-coming field I should check out. On a whim, I decided to join.

The club met weekly, and initially, it was very relaxed. We worked on projects using RStudio, a popular tool among data scientists for statistical analysis. One of the first projects I worked on with the club involved a simple analysis of S&P 500 time series data. It wasn’t anything too intense, but it was a great hands-on experience that got me hooked.

After college, I faced some challenges finding a role immediately. I didn’t have anything lined up, so I returned home and continued my job search. Fortunately, I landed a BI analytics role at a startup in the Bay Area. This position gave me solid experience and helped me build a strong foundation in the field.

From there, I moved into big tech, joining Fitbit as a capacity engineer. In this role, I managed the hosting infrastructure budget and helped teams plan their capacity needs, involving tasks like database management, scripting, and data engineering. It was a comprehensive role that significantly broadened my skill set.

For the past three years, I’ve been working as a data consultant, taking on projects with companies like Lyft and Cash App.

Most recently, I’ve accepted a senior data engineer position at Capital One, which I’m really excited about.

How did your job search start?

My job search process started around 2017. It was definitely a different landscape compared to now.

Back then, I followed the standard route of applying to numerous positions, hoping to get responses. I had some interviews, but the majority of my applications either went unanswered or were eventually rejected.

These days, with platforms like LinkedIn, job postings can receive hundreds of applications within hours, making the process even more competitive.

During my initial job search, I used websites like Indeed and Glassdoor. Interestingly, my first role didn’t come from the regular application process. Instead, someone reached out to me, possibly through email or LinkedIn, about a BI role. However, I didn’t do well in the interview and was told I didn’t pass.

Instead of accepting the rejection, I reached out and asked for feedback on what I lacked and how I could improve for future opportunities. The hiring manager appreciated my proactive approach and provided some useful insights.

After a few exchanges, he mentioned that he liked how I thought about and approached problems, which led him to give me a second chance.

He assigned me a take-home task involving SQL, which was relatively new to me at the time. I managed to complete it successfully, which then led to further tasks. This iterative process eventually resulted in my landing the role.

It wasn’t a straightforward path of mass applying and hearing back; it involved people reaching out to me and actively following up on feedback, even after rejections.

Can you highlight one of the most valuable experiences in your career?

One of my most valuable experiences was my time at Fitbit. I was exposed to a wide range of technologies and responsibilities. I worked with Python scripts that interacted with Google Sheets API, BigQuery, and Google Cloud Storage.

I also learned Docker, which allowed me to package scripts into Docker images and launch them as microservices or cron jobs. Additionally, I gained experience with deploying cloud resources using “infrastructure as a service” tools like Terraform and worked extensively with cloud platforms like GCP and AWS.

This exposure to various technologies and the opportunity to implement a self-service cloud cost dashboard for technical teams using custom SQL were invaluable in shaping my technical skills.

Another valuable experience was my role at Cash App. Unlike my technical roles, this position focused more on project management, helping new BI engineering teams with stalled or delayed projects and establishing processes for coordinating with stakeholders on key project milestones

This “trial by fire” experience taught me how to take the reins, manage timelines, and ensure project success despite challenges.

How did working across different departments at Fitbit help you in your career development?

Working across different departments at Fitbit significantly contributed to my career development. I had the opportunity to interact with engineering, management, C-level executives, and finance teams.

This cross-functional collaboration taught me how to communicate effectively with various stakeholders, summarize complex technical details into high-level overviews, and understand the broader business implications of technical decisions.

These skills were crucial in enhancing my ability to present and justify technical solutions to non-technical audiences, making me a more well-rounded professional.

Can you tell us about your experience at Cash App and how it differed from your technical roles?

My experience at Cash App was quite different from my technical roles. At Cash App, I was more focused on TPM (technical project management) than hands-on coding.

My role involved managing timelines, coordinating meetings, and ensuring BI engineering projects were on track. Many projects were stalled or delayed for various reasons, and my job was to identify the issues, coordinate with different teams, and drive the projects to completion.

This experience taught me the importance of project management skills and how to balance technical knowledge with organizational and leadership abilities.

What did you learn from your "trial by fire" experience at Cash App?

The “trial by fire” experience at Cash App taught me a lot about resilience and adaptability. It was a challenging role that required quick thinking and problem-solving, as well as pivoting if projects continued to stall or processes became obsolete.

I learned how to manage multiple projects simultaneously, navigate complex organizational structures, and communicate effectively with various stakeholders.

This experience also highlighted the importance of being proactive and taking ownership of projects, ensuring they move forward despite obstacles.

These skills have been invaluable in my career, helping me confidently tackle difficult projects.

How did your consulting role at Qbiz contribute to your career growth?

My consulting role at Qbiz was instrumental in my career growth. Working with high-profile clients like Lyft, Cash App, Reventus, and Kinship exposed me to a wide range of projects and technologies.

Being on the “bench” at Qbiz also allowed me to continuously learn and gain experience such as gaining cloud certificates and working on internal projects, even when not actively working on projects.

This role helped me develop a deep understanding of different industries, business needs, and existing technologies, enhancing my ability to deliver tailored solutions to clients.

It also provided me with a robust professional network and the ability to adapt quickly to new environments and challenges.

What motivated you to join Capital One, and how did you decide to leave Qbiz?

Capital One actually reached out to me, and the opportunity aligned well with my career goals. The company’s mission and the projects they were working on were fascinating; I would be helping build out a completely new piece of their internal data platform.

Additionally, everyone I spoke to at Capital One had been with the company for many years, indicating a supportive and stable work environment.

I did enjoy my time at Qbiz; my entire employment was spent gaining invaluable experience via interesting and engaging projects or completing certificates and working on internal projects.

Ultimately, it was a combination of career growth opportunities, financial incentives, and the desire to make a huge impact in a technical role that led me to join Capital One.

What are your long-term career goals, and how does Capital One fit into those plans?

My long-term career goals involve continuing to grow as a data engineer, taking on more leadership roles, and eventually leading large-scale projects or teams.

Capital One fits perfectly into these plans, as it offers a stable environment with opportunities for internal mobility and career growth. The company’s mission and the innovative projects they are working on are very exciting.

Additionally, Capital One’s supportive environment and excellent compensation package align well with my personal and professional goals, providing the stability and growth potential I’m looking for.

How do you view interviewing as part of your career development?

I view interviewing as a skill that needs regular practice and improvement. Each interview is an opportunity to learn and refine your responses.

Preparing for interviews through platforms like Interview Query, which offers structured learning paths and practice questions, has been immensely helpful. I treat interviews as a way to understand what skills are currently in demand and where I might need to improve.

Also, from my experience, when a recruiter reaches out to you, it can significantly ease the process because it means you’ve already passed the initial resume filtering. Keep in touch with recruiters as much as possible; getting your foot in the door this way can make a huge difference.

So, my advice would be to always follow up, seek feedback, and remain persistent and open to opportunities. Never be afraid to take an interview whenever they arise; you never know when an amazing prospect will come your way. At the very least, continuous interviewing helps keep your skills sharp and ensures you’re always prepared for new opportunities.

What advice would you give to someone starting their career in data science?

My journey into data science has been a mix of curiosity, persistence, and taking advantage of opportunities as they came.

For someone starting a career in data science, my advice would be to focus on gaining experience and building a strong foundation.

Joining clubs or groups, as I did with the data science club at UCSB, can provide valuable hands-on experience. Be open to different opportunities, including contract work or positions at startups, as they can be excellent stepping stones.

Networking is also key—connect with recruiters and professionals in the field, attend industry events, and leverage platforms like LinkedIn.

Additionally, continuous learning and staying updated with new tools and technologies will make you more competitive in the job market.