Data Engineer

New York
About Blink
Blink Health is fixing how broken, opaque, and unfair healthcare is. We are a New York based, mission driven, well-funded healthcare technology company. We’re changing healthcare through technology and transparency. With our proprietary technology, everyone now has access to one, low negotiated price on over 15,000 medications, but there is more work to do. We are a relentlessly learning, constantly curious, aggressively collaborative and cross functional team dedicated to inventing new ways of working in an industry that historically has resisted innovation. We're currently assembling the experience and talented team to get this done.

About The Team
Blink Engineering strives to build trusted, highly observable, data-driven products to bring affordable, accessible healthcare to all Americans. We understand healthcare is the most complex system most of us will ever fix. We believe in solving this complexity through the use of simple, well-known technologies. We are a highly collaborative team that believes in owning outcomes over owning code and putting patients at the center of everything we do.
Data Engineering is a small team delivering impactful insights. The team is responsible for building infrastructure, frameworks and tooling to enable data driven decisions; developing reports, dashboards, and metrics to provide accurate and timely information; and supporting various product and business groups with recommendation and in-depth analyses. Our data platforms are built using tools available on AWS including Redshift, Data Pipeline, and Spark.

About the Role
We are a small team of data generalists where everyone on the team works in the following areas:

Data engineering: Infrastructure, Frameworks and tooling to enable the company to be more data driven
Business Intelligence: develop reports, dashboards, and metrics to provide accurate and timely information.
Insights: support various product and business groups with recommendations and in-depth analyses.

In this role you will collaborate closely with our engineering team, performance marketing team, and business teams across the organization to provide accurate, timely data and efficient, impactful insights. You will also be working with external vendors and services.. By developing and maintaining the foundational data layer, you will have a direct, visible, and profound effect upon a data-driven organization that is revolutionizing the way people pay for prescription medicine.

Here is a sample list of tasks you may be asked to work on:

    • Design our next generation of data tools and frameworks in AWS
    • Develop and maintain data products and infrastructure
    • Develop efficient production code to perform tasks
    • Optimize system for performance
    • Develop Monitoring and Alerting framework to maximize uptime
    • Develop appropriate data models for landing, storing and merging data
    • Work with internal customers to develop optimized models and views for their needs
    • Guide analysts on high-quality efficient SQL
    • Guide the rest of the organization on best practices using our Data warehouse
    • Research, discover and PoC new technologies in the data organization
    • Develop business analysis solution in our BI tool
    • Work on in-depth analyses and discover data value

About You

    • Where you have previously worked or gone to school isn’t important to us. The following, however, is:
    • You have 2+ years of experience in Data Engineering.
    • You are an expert in SQL.
    • You are very interested in becoming a great data modeler. If you already are, that is great.
    • You have programed in a scripting language. If it’s Python, that is a big plus.
    • You have a good understanding of MPP databases. If you worked with one, that is a big plus.
    • You have a good sense of architecting systems. If you have worked with AWS, that is a big plus.
    • You understand why business uses BI Platforms. If you have worked with one, that is a big plus.
    • You understand Big Data principles, best practices and are genuinely interested in Big Data  landscape.
    • You are comfortable in a fast-paced, agile environment.