Principal Data Engineer
About Ledger Investing
Ledger Investing is a Y Combinator backed insure-tech startup that is transforming the way insurance risks are financed. Today, Ledger is an online marketplace connecting insurance risk to capital, focusing on securitization. Insurance risk originators are able to source capital more efficiently vs. the traditional value-chain. Capital providers gain access to an asset class that is highly diversified vs. most asset classes. Insurance securitization has quickly grown to be a $100 billion market but is limited in scope due to opacity and complexity. Ledger is expanding this market to $1 trillion by building a seamless data pipeline from the policyholder to the capital markets, enabling transparency, and bringing best-in-class analytics and real-time insights to the table. Our recent $75 million Series B round of investment funding has set us up for exponential growth. We are on our way to disrupting the industry by serving as an unparalleled, advantageous marketplace for virtually all types of insurance risks and capital, including traditional reinsurers, institutional investors, and accredited investors.
About the Team:
- The data platform team is a remote-first team building the data infrastructure that shape how people understand and handle billions of dollars of insurance risk
- Data Engineers at Ledger have the opportunity to touch every part of their tech stack
- We collaborate frequently with product thinkers, designers, sales, and domain experts to carefully craft valuable customer experiences
- We believe in collaboration, communicating often, and treating others with kindness and respect
- We believe everyone should have significant ownership and measurable impact
- We believe in continuously improvement and constantly evaluate what works and what doesn’t
- We believe in using modern tooling and technology to deliver the best developer experience possible
On the Data Platform team, you will:
- Define and develop the program and architecture for data collection, modeling, feature definition, data validation, model training, and reporting.
- Drive the collection of new data and the refinement of existing data sources.
- Create pipelines (ingestion, transformation, optimization, implementation, validation, governance)
- Develop processes and tools to monitor, analyze, and train models for performance and data accuracy (supervised/unsupervised training, backtesting)
- Define data schemas and services, focussed on accessibility/use-cases for the consuming client applications
- Work cross-functionally to define problem statements, collect data, build analytical models, and drive business solutions.
- Interest and ability in learning new techniques and research on how to apply them into daily work
- Work closely with product, design, and other engineering leaders to make sure we are executing on our product roadmap and building towards our long term goals
- Own effective and timely delivery of projects that contain significant ambiguity, requiring well designed solutions, and are key investments in the overall team roadmap
- Participate in the design review process, seeking and providing constructive criticism
- Participate in recruiting and mentoring great talent
- Be responsible for estimating and managing project timelines and risk
- We’re looking for someone with 10+ years of experience in data engineering or platform engineering with an emphasis working with creating data architectures to collect and analyze diverse datasets (e.g., large and small, structured and unstructured, behavioral and self-reported).
- Hands-on experience with several languages (R, Python, Java, Scala JS, SQL, etc.) not only to manipulate data and draw insights from diverse data sets, but also to integrate models into production services.
- History of delivering internal/production data tools for ETL, experimentation, exploration, cleansing, reconciliation.
- Working knowledge of OLTP and OLAP databases.
- Working knowledge of distributed data/computing tools: Map / Reduce, Hadoop, Spark, etc. and the data formats leveraged principally by these technologies (JSON, Parquet, Avro, Protobuf)
- Your interpersonal skills are exceptional. You have experience leading projects involving cross-functional and cross-cultural teams, fostering relationships across areas of the business that include Marketing, Sales, Product, and Engineering.
- Experience mentoring and taking an active part in helping make their peers and team better
- Provides technical advice and weighs in on technical decisions that impact other teams or the company at large. Researches and proposes new technologies
- An effective communicator both verbally and in writing
- Lead by example with a bias for action and set the standard for engineering excellence
- Ability to thrive with a high level of autonomy and responsibility
- BS/BA or greater in Mathematics, Physics, Statistics, Computer Science, Engineering, or another quantitative field.
- Experience with novel datastores (MySQL, Snowflake, Databricks, Redshift, RDS, NoSQL [binary/json], EMR, Sagemaker)
- Experience analyzing data from 3rd party providers: Hubspot, Google Analytics, Adwords, Amplitude, Segment, Salesforce, Pardot, Mandrill, Facebook Ads, etc.
- Experience visualizing/presenting data for stakeholders using: Looker, Tableau, D3, ggplot, etc.
- Familiarity with machine learning and statistical approaches (Stochastic Modeling)
- Experience with AWS, k8s, Terraform
- Domain knowledge in Financial services or Insurance
- Experience working in a scrappy, fast-moving tech environment
- Generous salary and equity compensation
- Work from anywhere. Our headquarters are in New York, but this position can be full-time remote.
- Unlimited paid vacation time
- Medical, dental, and vision insurance
- Gym membership
- $2,500 paid by Ledger towards your dream desk setup!
For US based positions:
Ledger Investing is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. We strictly prohibit and do not tolerate discrimination against employees, applicants, or any other covered persons because of race, color, religion, creed, national origin or ancestry, ethnicity, sex, gender (including gender nonconformity and status as a transgender or transsexual individual), sexual orientation, marital status, age, physical or mental disability, citizenship, past, current or prospective service in the uniformed services, predisposing genetic characteristic, domestic violence victim status, arrest records, or any other characteristic protected under applicable federal, state or local law.