Manager, Big Data Engineering
Pie's mission is to empower small businesses to thrive by making commercial insurance affordable and as easy as pie. We leverage technology to transform how small businesses buy and experience commercial insurance.
Like our small business customers, we are a diverse team of builders, dreamers, and entrepreneurs who are driven by core values and operating principles that guide every decision we make.
The Manager, Big Data Engineering will be a key leader within the Data Engineering team responsible for ingesting and analyzing vast amounts of data, helping Pie efficiently evaluate risks for our small business owners. In this role, you will oversee the integration of millions of structured and unstructured data points from multiple sources (internal and external) into a big data ecosystem.
You will build a big data ecosystem that will contain three fundamental elements: an extensive data footprint, delivery at scale, and AI-driven intelligent data management. The ecosystem will process data from a diversity of sources including consumer intelligence, social media, credit information, retail history, geographic location tracking and telematics, mobile, satellite, behavioral monitoring, psychographic, biographic, demographic, and firmographic data, sensors, and wearable devices.
It will be the Manager's responsibility to ensure this big data ecosystem can be leveraged for machine learning, data science, and advanced analytics to make light-speed decisions in the following areas:
- “Predicting the future” using Predictive Modeling
- Ability to gain insights into customer behavior
- Building a trusted relationship with customers
- Accurately judging risks
- Spotting anomalies fast
- Enhanced Fraud Detection
- Automated Claims Processing
- Improved Medical History Analysis
- New Business Opportunities
- Understanding Market Conditions
This position requires a technical leader who is eager to drive a strong engineering vision and can scale the technology while fostering a collaborative, inclusive culture and should have an overall desire to help develop team members along their career path.
How You’ll Do It
- A hands-on leader who oversees the integration of both internal and external data sources to leverage machine learning, data science, and advanced analytics
- Collaborates and coordinates with multiple departments, stakeholders, partners, and external vendors
- Designs modern architectures where raw data is transformed into high-impact information, and translates business needs into structure that fits the data/information flow within the organization
- Collaborates as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications
- Leverages big data and analytics to help create and strengthen a culture of transparency and drive innovation through partnerships
- As a People Leader, you will be responsible for building a world-class data engineering team as well as mentoring, coaching, providing feedback, building career plans and assessing performance for your direct reports.
- Partners with Product Management to translate product vision into product strategy
- Owns the strategy and execution of a product roadmap for a big data ecosystem that manages, curates and delivers high quality IoT data and services.
- Collaborates with data engineers, Machine Learning (ML) engineers, software engineers, data scientists, and User Experience engineers to support solutions delivered to our business partners
- Builds data collection framework that will drive 360 degree insights into customer experience, risk selection, and segmentation
The Right Stuff
- You have 6+ years of experience leading a technical team on deliverables and/or project functions/areas with a strong desire to mentor, coach, and develop engineers
- You have experience with bringing data into a centralized data repository or manipulating the available data to build additional data sets for Analytics and Reporting purposes
- You have a solid understanding of data structures, query design, data modeling, and extensive experience with SQL across multiple platforms
- You enjoy helping teams push the boundaries of analytical insights, creating new product features using data, and powering machine learning models
- You have experience focused on batch and real-time data pipelines development, data processing/data transformation using ETL/ELT tools, Snowflake, Airflow and DBT
- You apply a test-and-learn mindset to data architecture with experimentation of different components and concepts
- You have experience building and deploying large-scale AI Engineering platforms that allow for deployment and scalability of machine learning models
- You have knowledge with engineering and research best- practices for scaling ML-powered features, with a goal to enable the fast iteration of and efficient experimentation with novel features
- You have experience creating data assets by using image processing, object detection and localization, speech recognition, natural language processing, recommendation systems, forecasting, and multimodal learning
- You are comfortable working in a rapidly changing environment with ambiguous requirements, and taking intelligent risks
- Experience with Web and Product Analytics (Google Analytics, Mixpanel, Amplitude, or other)
Preferred Experience
- Experience in a fast paced technology start-up
- An understanding of the insurance industry and products
- Able to establish a strong MLOps culture and set of practices for managing the entire lifecycle of ML systems through integration, testing, release, deployment, and infrastructure automation
Base compensation range for position: $160,000 - $220,000
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Base Compensation Range
$160,000—$220,000 USD
- Competitive cash compensation
- A piece of the pie (in the form of equity)
- Comprehensive health plans
- Generous PTO
- Future focused 401k match
- Generous parental and caregiver leave
- Our core values are more than just a poster on the wall; they’re tangibly reflected in our work
Our goal is to make all aspects of working with us as easy as pie. That includes our offer process. When we’ve identified a talented individual who we’d like to be a Pie-oneer , we work hard to present an equitable and fair offer. We look at the candidate’s knowledge, skills, and experience, along with their compensation expectations and align that with our company equity processes to determine our offer ranges.
Each year Pie reviews company performance and may grant discretionary bonuses to eligible team members.
Location Information
Unless otherwise specified, this role has the option to be hybrid or remote. Hybrid work locations provide team members with the flexibility of working partially from our Denver or DC office and from home. Remote team members must live and work in the United States* (*territories excluded), and have access to reliable, high-speed internet.
Additional Information
Pie Insurance is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, marital status, age, disability, national or ethnic origin, military service status, citizenship, or other protected characteristic.
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