Senior Manager, Data Engineering

Data Engineering Leader

Founded in 2017, NinjaHoldings works to give everyday Americans better access to financial services than traditional institutions typically provide. Through our CreditNinja and NinjaCard brands, we offer digital banking and lending products designed for consumers often overlooked, paired with incentives that support long-term financial improvement. Our Edge brand extends this expertise to other companies, providing underwriting, fraud detection, and analytics services. Headquartered in Chicago with a distributed global workforce, we are a lean, growing organization committed to advancing consumer finance in the US.

This position will lead the team responsible for the data platforms and pipelines that power reporting, analytics, operational decision making, and future AI capabilities across the company.

This is a technical leadership role focused on setting direction, developing the team, and making sure our data platform continues to evolve with the needs of the business. The person in this role should have enough technical depth to step in when needed, participate in architecture discussions, review designs, and help solve difficult problems.

Our current stack includes Snowflake, dbt, Fivetran, Meltano, PostgreSQL, and AWS. We are also modernizing our warehouse architecture around a Medallion model and building a stronger foundation for analytics and AI.

We are looking for someone who sees Data Engineering as a platform capability for the entire company, not simply a team that maintains pipelines and supports reporting. The right person will think beyond today's reporting requirements, build reliable systems today, and make architectural decisions that give us more options tomorrow. We want someone who can help us build a data platform that will support the company several years from now, including larger data volumes, more advanced analytics, automation, and AI powered applications. That means making data easier to trust and use, improving the effectiveness of the team, and keeping the platform scalable and cost effective.

Key Responsibilities:

• Lead the Data Engineering team and set the technical direction for our data platform
• Own the architecture, reliability, performance, and evolution of Snowflake, PostgreSQL, and the pipelines that move data across our systems
• Lead our transition to a Medallion architecture and establish clear standards for how data is ingested, transformed, modeled, tested, documented, and consumed
• Own and evolve our modern data stack, including Snowflake, dbt, Fivetran, Meltano, PostgreSQL, AWS, and related technologies
• Partner with application engineering teams on transactional database design, schema changes, performance, scalability, and reliability
• Work with Engineering, Analytics, Product, Finance, Risk, Marketing, and other business teams to turn data needs into reusable, well designed solutions instead of one off reporting work
• Establish strong engineering practices around data quality, automated testing, observability, lineage, security, documentation, and incident response
• Improve self service access to data so teams can safely understand and use data without relying on Data Engineering for every request
• Monitor and optimize the platform for performance, scalability, and cost
• Build a long term roadmap that balances current business needs with the future of the platform, including AI use cases

Leadership Responsibilities:

• Lead, mentor, and develop a strong team of Data Engineers
• Set clear technical standards and expectations while giving engineers ownership of their work
• Participate in architecture and design decisions, challenge assumptions, and step in technically when needed
• Help the team prioritize work based on business impact, technical risk, reliability, and long term value
• Create a culture where data quality, testing, documentation, and operational reliability are treated as part of the product
• Communicate technical decisions, tradeoffs, risks, and investments clearly to both technical and nontechnical teams

Ideal Candidate Will Have:

• 6+ years of experience in Data Engineering, Data Platform Engineering, Database Engineering, or a related field
• 2+ years of experience leading or managing Data Engineers or other technical teams
• Strong experience with Snowflake, dbt, SQL, and modern ELT or ETL architectures
• Strong understanding of PostgreSQL or similar relational databases, including schema design, indexing, query performance, and reliability
• Experience with data ingestion and integration tools such as Fivetran, Meltano, or similar technologies
• Experience with dimensional modeling, Medallion architecture, or other modern warehouse design patterns
• Strong understanding of data quality, automated testing, observability, lineage, governance, and security
• Experience operating cloud based data platforms and understanding performance and cost tradeoffs
• Ability to think at both the architecture level and the implementation level when needed
• Strong communication skills and the ability to work effectively across Engineering, Analytics, business teams, and leadership

Additional Pluses:

• Experience with Python or Ruby for automation, tooling, or data processing
• Experience in financial services or another regulated industry
• Experience supporting analytics or AI applications
• Experience with data catalogs, data contracts, or master data management
• Experience leading a significant warehouse or data platform modernization effort
• Experience using AI and automation to improve engineering productivity, monitoring, documentation, or data quality

Benefits & Perks:

• Flexible Paid Time Off
• Health Benefits with generous medical, dental and vision insurance plans
• 401(k) with matching contribution
• Paid Family Leave
• Annual Wellness & WFH Subsidies
• Employee Referral Program
• Remote first culture with convenient downtown office in the heart of the city