MANTL is a fast-growing NYC-based FinTech SaaS company on a mission to build technology that will help America’s financial institutions and their communities thrive. Think Shopify or Squarespace, but purpose-built for community banks and credit unions. We are drastically changing the landscape through modern banking software that empowers banks and credit unions to grow digitally.
Our flagship product, Online Account Opening, has quickly become considered best in class in our industry, showing clear and material performance beyond any of our competitors. Suffice it to say, our customers love MANTL.
Since launching our first product in 2017, we have built several new products, thoughtfully grown the team, and have become a market leader.
Who makes up our team?
People are our most important asset and the number one reason we all love working at MANTL. As a team, we value accountability, transparency and collaboration. We have agile teams, with clear, outcomes-focused goals.
We’re a group of passionate people with diverse backgrounds and skill sets with a unified goal – growing MANTL. We support an open and transparent culture that helps foster productive and engaging discussions. We want to work with inclusive people who understand the importance of treating their colleagues exceptionally well – people who will gladly go out of their way to help others with things big and small.
We are always a work in progress and love hearing feedback from our team.
Data Engineer| What You Will Do
As a Data Engineer, you’ll be responsible for building the foundation for our data at MANTL, building out data infrastructure which will enable users across Product, Sales, Marketing, Customer Success, and Finance, enable marketing campaign analytics, user-level and field-level data management, report building, attribution, revenue forecasting, lookalike modeling, and powering new revenue opportunities. You will work primarily in GCP, SQL, BigQuery, Python, and DBT. Experience with data migrations is a requirement and experience with data warehouse build-out is a plus.
Who You Are
- You are a SQL whiz with 5+ years of experience in different flavors of SQL (BigQuery, Postgres, others).
- You have 5+ years of experience performing data cleansing and validation, data model creation and enterprise data warehouse setup and maintenance, and Extracting, Loading and Transforming large datasets from a variety of data sources
- You can build and maintain data flow processes from internal and external sources, assist in data management, migration, governance, and business rules to ensure data integrity across different channels/platforms
- You have extensive experience with data migrations and developing associated testing and documentation
- You have extensive experience with data management, row- and field-level security and permissioning, and maintenance strategies
- You have multiple years of experience in Google Cloud Platform, BigQuery, and Looker
- You have many years of experience writing complex SQL queries and are intimately familiar with performance constraints and optimization for large workloads
- You have multiple years of experience writing Python scripts and data pipelines in Pandas
- You have multiple years of experience building and maintaining data pipelines in DBT, Oozie and similar tools
- You’re familiar with Microservice Architectures, Domain-Driven Design, and Event-Driven Architecture
- You have experience setting up and managing BigQuery as an EDW for a medium-sized organization
- You can pull and analyze product usage data and provide insights for content and campaign development
- You have experience working closely with Business teams to identify automation needs and support the continuous improvement of our business by designing, tracking, and analyzing the impact of marketing campaigns, product feature development, and customer success efforts, among others
- You have experience building and maintaining dashboards, KPI/metric reports, and other data visualizations
- You can effectively communicate analytical results to non-technical team members by explaining the story behind the data and make recommendations to the business based on data insight
We don’t expect you to have all of these things – but we do expect you to be exceptional at some or most. Tell us what those are.