Senior Data Engineer

Data is at the heart of decision-making for every team at M1, and that makes data engineering a uniquely impactful and fast-paced role. As engineers, we bring passion and craftsmanship to our work, and we hold data and analytics engineering to the same high standard of technical excellence as the rest of M1.

Our culture is built on Extreme Ownership. We work through complex technical problems together, and everyone on the team is empowered to make architectural decisions and take end-to-end responsibility for their outcomes. We are looking for a Senior Engineer who thrives in this environment—someone who is not just a high-level individual contributor, but a technical leader who elevates the entire team.

The Role

A competitive applicant for this role will be a versatile generalist with deep expertise in SQL, Python, and data warehousing. However, technical proficiency is only half the equation; success in this role requires a high degree of systems-level curiosity. We are looking for an engineer who is unafraid to venture into undocumented territory and who seeks to understand the systems that live "outside the walls" of the data platform. Whether it’s diving into the source code of our banking core or collaborating with brokerage operatives to understand financial mechanics, you should be driven to understand the how and why behind the data you manage.

Our data ecosystem is built on a mature, cloud-native architecture designed for scale and reliability. We leverage AWS and Kubernetes for our infrastructure, with S3 and Redshift forming the foundation of our data lake and warehouse. Our modeling and orchestration are powered by dbt and Airflow, with Superset driving our business intelligence. While these tools are our current foundation, we are a team of builders who are constantly evaluating the right tools for the next phase of M1’s growth.

What You’ll Do

• Drive Architectural Strategy: Help lead the design and implementation of scalable, cloud-native data pipelines and architectural blueprints using Python and Kubernetes.
• Exercise Extreme Ownership: Take full accountability for the data lifecycle, from initial design and implementation to long-term maintenance and optimization.
• Build Self-Service Platforms: Create and maintain the infrastructure that enables stakeholders across M1 to solve real-world problems independently.
• Mentor and Lead: Grow alongside a committed team of engineers by leading design sessions, performing rigorous code reviews, and setting engineering standards.
• Collaborate Across Functions: Partner with brokerage, banking, and product teams to translate complex business needs into automated, high-integrity data processes.
• Ensure Data Excellence: Identify and integrate new data sources into our lake and warehouse, ensuring high levels of data quality, observability, and security.
• Continuous Improvement: Proactively identify technical debt and execute on opportunities to improve the performance and reliability of existing systems.

Qualifications

• 5+ years of experience in data engineering, backend software engineering, or a related field.
• Expert-level SQL and Python: Experience building production-grade ETL/ELT pipelines.
• Innate Curiosity: A proven track record of stretching beyond a standard job description to understand the broader technical ecosystem and business context.
• Modern Engineering Mindset: An interest in leveraging AI to amplify your personal productivity and a willingness to contribute to the team’s adoption of AI tooling.
• Hands-on Experience with our Core Stack: Proven experience with dbt, Apache Airflow, and AWS (or a similar cloud environment).
• Architectural Mindset: Ability to design systems that are scalable, maintainable, and adhere to industry best practices.
• Extreme Ownership: A self-motivated, entrepreneurial spirit with a desire to run with projects from conception to completion.
• Excellent Communicator: Ability to explain complex technical trade-offs to both engineers and non-technical stakeholders.

Preferred Qualifications

• Practical AI Experience: Experience building or deploying infrastructure to support LLMs, vector databases, or machine learning models in a production environment.
• Fintech Expertise: Experience in the securities, banking, or broader financial services industries.
• Infrastructure as Code: Experience with Terraform and managing cloud infrastructure.
• Big Data Ecosystems: Experience with S3, Redshift, Snowflake, Presto, or similar systems.
• Streaming Data: Experience with real-time, event-driven data systems (e.g., Kafka, Kinesis).
• Data Governance: Knowledge of data privacy, security, and quality frameworks in a regulated environment.
• Domain Passion: A general knowledge of investing and personal finance or a strong desire to learn the industry.

Salary Band: $170,000 - $200,000

Additional Information

Our Values 

Our team embodies our ten core principles and if these principles speak to you – we’d love to talk with you. 

• Mission driven Wealth expands what life can be. We exist to help people build it, optimizing with intelligence and precision so their resources become fuel for possibility. This is work worth doing.

• Extreme ownership We own outcomes, not just tasks. When something affects our clients, teammates, or shareholders, we take full responsibility. No excuses, no finger-pointing, no waiting for someone else to act.

• Boldness Thinking small is a self-fulfilling prophecy. We set ambitious goals because they inspire ambitious results. We would rather fail at something meaningful than succeed at something trivial.

• Ruthless prioritization Our ambition will always exceed our capacity. We say no to good ideas so we can pursue great ones, and we use time as a constraint that forces the choice. Generous timelines don't prevent delays; they invite sprawl.

• Integrity We tell the truth: to clients, to each other, to ourselves. We are direct about trade-offs, honest about risks, and unapologetic about what we believe. Trust is earned through clarity, not comfort.

• Effectiveness Intelligence and leverage are how we do more with less. We care about results, not activity. Whatever it takes to deliver, whether that demands disciplined process or resourcefulness.

• Team over self We achieve more together than alone. We hire people who elevate others, we share credit generously, and we treat a teammate's problem as our own.

• Transparency We share information openly, communicate simply, and provide the context people need to make good decisions fast. No hoarding, no politics, no spin.

• Momentum Perfection is a direction, not a destination. Crawl, walk, run, sprint. We make consistent progress with the speed and precision a financial institution demands.

• Resilience Big goals come with setbacks. Markets turn, plans break, timelines slip. We adapt without losing resolve, treating obstacles as problems to solve rather than reasons to quit.

Our Perks 

• Competitive Pay and Stock Options 

• Comprehensive health, dental, vision, disability, and life insurance 

• Retirement benefit with employer match 

• Unlimited PTO 

• Transparent and open communication with leadership 

M1 is an equal opportunity employer and values diversity across the company. M1 does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.