Data Engineer, Machinify
Infra
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AI & data-driven healthcare cost reduction platform
Open for applications
AI & data-driven healthcare cost reduction platform
101-200 employees
Open for applications
We sponsor visas
101-200 employees
Company mission
To develop software that helps people get the right medical care, at the right time, at the right price.
Role
Who you are
- 7+ years of experience as a Data Engineer / Software Enginer / Platform Engineer, with strong expertise building internal tooling and frameworks
- Proficient in Python and SQL
- Deep expertise with Apache Spark (core processing engine today)
- Advanced experience with Apache Airflow
- Experience building monitoring & observability systems (Grafana, ELK Stack, or DataDog)
- Experience designing and implementing data validation & testing frameworks at scale
- Strong understanding of AWS (primary cloud environment)
- Proficient in Kubernetes and modern orchestration patterns
- Deep understanding of schema evolution, data modeling, and versioning for large-scale data platforms
- Proven ability to operate as a Staff/Lead: driving technical strategy, mentoring others, and collaborating cross-functionally
Desirable
- Experience working with Kafka, Spark Streaming, or other modern streaming platforms
- Scala experience (Spark internals, performance tuning, advanced transformations)
- Familiarity with metadata management tools such as DataHub, Amundsen, or OpenMetadata
- Experience using GenAI to improve data engineering workflows and developer experience
- Experience building unified data platforms post-merger
- Exposure to GCP or multi-cloud environments
What the job involves
- As a Staff/Lead Data Engineer, Infra, you will play a pivotal role in enabling every data engineer to be faster, more reliable, and more productive
- You will build the core frameworks, tools, and observability systems that:
- Abstract common pipeline patterns into reusable components
- Implement robust monitoring and testing across the platform
- Drive testability and data quality at scale
- Unify tooling and standards across our post-merger environment
- Explore the use of GenAI to further accelerate data engineering productivity
- You’ll collaborate deeply with Data Engineers, Data Scientists , Platform Engineers, ML, Product, and SMEs to shape the foundation of our next-generation data platform
- Develop and maintain internal DE SDKs / libraries to abstract and standardize Spark + Airflow patterns
- Design and implement pipeline testing frameworks to enable CI/CD-based data validation
- Create pipeline observability & monitoring systems (Grafana, ELK, DataDog) to ensure reliability and visibility
- Drive adoption of data validation frameworks to automate and scale data quality enforcement
- Lead initiatives to unify our data platform post-merger by defining scalable standards and patterns
- Partner with Data Engineers and SMEs to improve canonical modeling, schema evolution, and data versioning
- Help architect centralized metadata management to replace fragmented, ad-hoc systems
- Leverage GenAI and modern tooling to improve pipeline development, monitoring, and debugging
- Prototype new ways to improve developer productivity, data quality and pipeline reliability using emerging technologies
- Work with core Data Engineers to identify and address productivity bottlenecks and scaling challenges
- Support customer data onboarding frameworks indirectly through improved tooling and processes
- Partner closely with Platform/Server Engineering to build/request new features
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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