Veryfi empowers organizations to transform their unstructured data in the form of receipts, invoices, purchase orders, checks, W2s and other business documents into structured data at scale. Their suite of data transformation APIs can be leveraged for many use cases in financial services to deliver valuable business intelligence in seconds. Trusted by enterprises and technology companies alike, Veryfi’s AI-based platform is being leveraged by companies worldwide.

Veryfi is backed by NewView Capital (NVC), Act One Ventures, TI PLatform, Y Combinator and Zillionize

Veryfi Raises $12 Million To Use AI To Tackle The Unstructured Data Entry Market https://www.forbes.com/sites/rebeccaszkutak/2021/04/26/veryfi-raises-12-million-to-use-ai-to-tackle-the-unstructured-data-entry-market/?sh=886fe19183f8

The Untapped Potential of Unstructured Data https://nvc.vc/perspectives/veryfi-the-untapped-potential-of-unstructured-data/

Capterra Reviews https://www.capterra.com/p/141684/Veryfi-Receipts-and-Expenses/reviews/

COME AND SAY G'DAY!

Veryfi is looking for our next great data engineer that will build out and scale our analytics platform and corresponding data pipelines. Responsible for building and scaling a robust platform that will deliver our ML/AI driven insights to coordinate with the data visualization team to create engaging and insightful content

Responsibilities:

• Craft data engineering components, applications and entities to empower self-service of our big data

• Develop and implement technical best ETL practices for data movement, data quality and data cleansing

• Optimize and tune ETL processes, utilize reusability, parameterization, workflow design, caching, parallel processing, and other performance tuning techniques.

Qualifications:

• Knowledgeable about data engineering best practices, comfortable in a fast-paced startup

• Experience with data warehousing, streaming data and supporting architectures: pub/sub, stream processor/data aggregator, realtime analytics, data lake cluster computing framework

• Master of components necessary to architect solutions for complex data platforms, and large scale CI/CD data pipelines using a variety of technologies (REST APIs, Advanced SQL, Amazon S3, Apache Kafka, Data-Lakes, etc.), relational SQL DBs (e.g. MySQL, Postgres), newer (e.g. Mongo, Neo4j) to in-memory caches (e.g. Redis, Memcache)

• Working knowledge of distributed computing and data modeling principles.

• Experience with object-oriented design and coding and testing patterns, including experience with engineering software platforms and data infrastructures.

• Experience in Big Data, PySpark, Streaming Data.

• Knowledge of data management standards, data governance practices and data quality dimensions.

• Experience in UNIX systems, writing shell scripts and programming in Python

• Hands on experience in Python using libraries like NumPy, Pandas, PySpark.

(a) Native Mobile apps: Swift, Objective-C & Kotlin

(b) Backend: Python 3, TensorFlow, APIs on Django, Hub/Web on Flask

(c) IaaS: AWS with auto deploys to 4 geographies (read the deployment posts by Andrew here https://medium.com/the-road-to-silicon-valley)

(d) Database: Amazon Aurora