Come join Lease End and help revolutionize auto financing! We are a young, profitable FinTech startup in the heart of Silicon Slopes growing organically. Work with a talented team and enjoy a 4-day work week! Lease End helps people buyout their auto leases and capture vehicle equity without having to go into the dealer or DMV. We are also focused on innovating in the AI and DeFi space to scale financing and provide our users with more options.

We're looking for a Database Engineer / Data Scientist with 3-5+ years of experience to help us build out our data lake / warehouse, enhance business intelligence and use ML/AI to accelerate our business. We have a good foundation but are looking to take our data infrastructure and performance to the next level. You'll focus on our database design & performance, building and enhancing our data pipelines, building out our data lake / warehouse, and laying a founding for ML/AI models.

Our data tech stack is Python, Apache Spark (Databricks) and PostgreSQL (Aurora on AWS). Our business tech stack is React, Node.js, TypeScript, PostgreSQL and GraphQL. We leverage AWS with a current focus on CloudFront, ECS, Aurora (PostgreSQL), SQS and Lambda. You'll need to think through and solve complex problems and effectively implement solutions.

We enable our teams to craft and release great code by providing plenty of deep-focus work time, minimizing meetings, focusing on value-add features, pushing frequent releases, and recharging with 3-day weekends.

Responsibilities

Design and Develop Data Pipelines: create efficient and scalable data pipelines for ingesting, processing, and transforming data using tools like Apache Spark, Apache Kafka, or similar technologies.

Oversee Data Pipeline Operations: Monitor and manage the health, performance, and reliability of data pipelines. Implement error handling, logging, and alerting mechanisms to ensure data integrity. Perform root cause analysis and resolve data-related problems promptly.

Exploratory Data Analysis (EDA): Conduct in-depth EDA to gain insights into the data, identify patterns, anomalies, and potential data quality issues. Utilize data visualization tools and techniques to communicate findings effectively.

Data Preparation for ML/AI: Clean, preprocess, and feature engineer datasets to prepare them for machine learning (ML) and artificial intelligence (AI) model development.

Machine Learning Model Deployment: Deploy ML models into production environments, ensuring they are integrated seamlessly with data pipelines and business applications.

Performance Optimization: Optimize data processing workflows and queries to improve performance and reduce latency. Identify and implement optimizations to enhance the efficiency of Spark on Databricks.

Data Governance and Security: Implement data governance policies, access controls, and encryption mechanisms to protect sensitive data. Ensure compliance with data privacy regulations (e.g., GDPR, HIPAA).

Documentation and Collaboration: Maintain documentation of data pipelines, processes, and code. Collaborate with cross-functional teams, including product managers, and business stakeholders.

Continual Learning and Innovation: Stay up-to-date with the latest advancements in data engineering and data science. Identify opportunities for innovation and recommend new technologies or methodologies to enhance data capabilities.

Contribute to a positive culture of innovation and problem solving

Qualifications

Bachelor's degree or equivalent real-world experience in Data Engineering

3-5+ years of professional experience working specifically with data engineering or data science and the modern data tech stack.

Experience with the following technologies: Python, Apache Spark (Databricks), Delta Lake, SQL

Solid experience managing data pipelines (ELT), performing data analysis, working with both relational and unstructured data, and preparing data for ML/AI models.

Experience with ML/AI technologies is also important.

Advanced communication skills both verbal and written

Detail oriented with critical thinking skills

Must be able to work well in a fast-moving startup environment

Benefits:

401(k) and 401(k) matching
Health insurance
Dental insurance
Vision insurance
Health savings account
Life insurance
Supplemental insurances

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Data Engineer/Data Scientist