Senior Data Engineer

We are seeking a highly motivated Senior Data Engineer to join the MoneyLion Data Platform & Martech Engineering team. This role will be responsible for designing, building, and scaling the data foundations that power analytics, customer engagement, marketing activation, AI initiatives, and financial product experiences across the organization.

The ideal candidate combines strong software engineering fundamentals with expertise in data architecture, dimensional modeling, semantic layer design, and modern cloud data platforms. This individual will play a critical role in enabling trusted, governed, and scalable data products while partnering closely with Product, Martech, Analytics, Data Science, and Engineering teams.

As part of a forward-thinking organization, we are looking for engineers who embrace AI-assisted development and are excited about building intelligent systems, automation, and agent-powered solutions that improve business outcomes and engineering productivity.

- Design, build, and optimize scalable batch and streaming data platforms, ETL/ELT frameworks, and AI-ready data pipelines supporting analytics, marketing, product, and operational use cases with strong focus on reliability, observability, scalability, and cost optimization.

- Architect and maintain enterprise-grade data models and semantic layer architectures using Kimball dimensional modeling methodologies, including fact/dimension design, conformed dimensions, slowly changing dimensions (SCDs), star schemas, and governed business metrics.

- Partner cross-functionally with Product, Martech, Analytics, Data Science, and Engineering teams to translate complex business processes into scalable data contracts, integration patterns, and trusted analytical models supporting attribution, audience intelligence, experimentation, personalization, and data activation.

- Design and support Martech and customer data infrastructure, including platforms such as Hightouch, Segment, Iterable, Amplitude, and other activation technologies, enabling audience orchestration, customer journey automation, reverse ETL, and real-time marketing use cases.

- Build and operationalize AI-powered solutions, intelligent agents, and data products that improve internal productivity, customer engagement, campaign optimization, and self-service access to data and insights.

- Define and enforce platform standards for schema evolution, data lineage, governance, metric consistency, access controls, naming conventions, and data quality SLAs across the organization.