Data Engineer, Machinify

Infra

$220-250k

Plus equity

SQL

AWS

Docker

Kubernetes

GCP

Python

Kafka

Airflow

ELK

Spark

Grafana

Senior and Expert level

San Francisco Bay Area

Remote from US

We sponsor visas

AI & data-driven healthcare cost reduction platform

Open for applications

AI & data-driven healthcare cost reduction platform

101-200 employees

HealthcareB2BArtificial IntelligenceBig dataDeep TechAnalyticsMachine LearningSaaS

Open for applications

$220-250k

Plus equity

SQL

AWS

Docker

Kubernetes

GCP

Python

Kafka

Airflow

ELK

Spark

Grafana

Senior and Expert level

San Francisco Bay Area

Remote from US

We sponsor visas

101-200 employees

HealthcareB2BArtificial IntelligenceBig dataDeep TechAnalyticsMachine LearningSaaS

Company mission

To develop software that helps people get the right medical care, at the right time, at the right price.

Job

Company

Role

Who you are

Deep experience as a hands-on Data Engineer building production data pipelines
Experience managing the delivery of complex data
Experience in ETL orchestration and workflow management tools with a strong preference for Apache Airflow
Experience in Spark or other distributed computing frameworks
SQL and Python
Advanced SQL performance tuning
Kubernetes and building Docker images
AWS & GCP
Experience working with APIs to collect or ingest data
Manage SLA for all pipelines in allocated areas of ownership
Streaming technologies like kafka , spark streaming etc
ELK stack , Grafana etc

What the job involves

We are seeking a Staff/Lead Data Engineer to build and own critical data pipelines
Independently understand all aspects of a business problem including those unrelated to their area of expertise, weigh pros and cons of different approaches and suggest ones likely to succeed
Work with a cross-functional organization including engineering, delivering, subject-matter experts, product managers, as well as platform engineers to deliver a scalable framework
Map the customer data into Machinify canonical form. Identify and ingest non canonical fields and generalize the process to a minimal level of customization
Proactively design and adapt the canonical form to suit changing query patterns and needs
Ultimately own data availability and quality for the Data Science organization

Our take

Founded in 2016, Machinify's original aims were to help re-tool business operations across industries, transform data into decisions, and enable established enterprises to keep up with the rapidly digitizing space. Nowadays, the company has pivoted to employ its AI expertise specifically in the healthcare industry, where it has already found success with Payers and secured several market-leader customers.

Healthcare is one of many industries where companies have vast pools of data but struggle to make the most of it due to operational restraints in deploying AI systems. Machinify makes it easier for Payers to implement AI-powered decision-making, applying it to the authorization of treatments, review of medical claims and bills, and diagnosis of underlying conditions.

The company's choice to focus on healthcare comes alongside a more pinpointed mission to help tackle overpayment and supply more affordable healthcare to a broader scope of patients, which is definitely commendable. With intelligent applications such as those Machinify provides seeing broader adoption in the market, the company will likely see more funding and growth in the coming years.

Steph

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 3 rounds)

Oct 2018

$10m

SERIES A

Mar 2016

$2.8m

SEED

Total funding: $15.6m

Company benefits

Work from anywhere in the US
Home office stipend
Work on big projects that impact millions of lives
Premium medical, dental & vision benefits
401k plan sponsorship
No-meeting day every week
Individual Equity and Tax Advisory services
Flexible PTO
Home office stipend
Mentorship from industry leaders
Annual learning and development stipend

Company HQ

University South, Palo Alto, CA

Leadership

Prasanna Ganesan

(Co-Founder & CEO)

Previously co-founded VUDU where they served as the CTO and General Manager. They also served as the CTO at Klip before founding Machinify.

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