Manager – Big Data Engineering
Posted on 3/29/2023
Pie Insurance

201-500 employees

Small business insurance platform
Company Overview
Pie's mission is to empower small businesses to thrive by making commercial insurance affordable and as easy as pie. The company leverages technology to transform how small businesses buy and experience commercial insurance.
United States
Experience Level
Desired Skills
Data Analysis
Data Science
Data Structures & Algorithms
Google Analytics
Data & Analytics
  • 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)
  • “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
  • 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
  • (
  • Territories excluded), and have access to reliable, high-speed internet
Desired Qualifications
  • 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