Position: Data Engineer/Datawarehouse Engineer
Company: Very Good Security
Category: Data Engineer
Experience required: 2y
English level: fluent

In this role you will:
- Partner with business teams to scope, design, execute, measure, and increase the impact of well-informed decisions based on data solutions to empower data-driven and data-informed business strategies of high complexity and scope 
- Research & Improve the data quality of usable data models within the Data Warehouse and report data anomalies in issues to source system owners and the Data Engineering team 
- Build end-to-end data solutions, including data pumps, data models, and data quality reports to  enable self-service in Business Intelligence or Systems 
- Deliver well defined, high quality, transformed, tested, and documented data sets in our Enterprise Dimensional Platform to empower our VGS Business teams to self-serve and answer their own questions
- Own, Build, Improve, Optimize and Maintain a strong Business Intelligence and Analytics Platform & Infrastructure (especially Database/Data Warehouse Platform) via version control, data quality test/reports, ad-hoc reports, and high-quality data models for self-service consumption, keeping Data Privacy & Security in mind while improving VGS overall data architecture and management practices & implementations 
- Peer review and craft code that follows our software development process and meets our internal standards for style, maintainability, and best practices for a high-scale database environment. Maintain and advocate for these best-practice standards through code review, while keeping reliability, performance, scalability, security, automation, and version control in mind
- Document every decision/action in issues, pull requests, data documentation, READMEs, or in Confluence to cultivate a knowledge-sharing environment across multiple timezones 

We expect you to have:
- 2+ years of experience in Data Warehousing, Business Intelligence, and Data Quality using strong SQL, Python skills, and data artifacts 
- Experience with Enterprise Dimensional Modeling and data analytical methodologies (including Funnel Analysis, Behavioral Analysis, Benchmarking, Segmentation/Growth Reporting, Forecasting) 
- Demonstrate capacity to clearly and concisely communicate complex business logic, technical requirements, and design recommendations through iterative solutions
- Familiarity with (Git) version control, command line, and AWS Data products 
Strong interest in data quality and detail-oriented with basic math & statistical knowledge 
- Experience working with cross-functional stakeholders in a highly agile, intensely iterative environment with a positive, self-motivated, and solution-oriented mindset
- English - Advanced

Bonus points for:
- Experience developing data pipelines, ELT/ETL processes, and Data - Modeling/Architecture best practices
- Familiarity with Matillion, Argo Workflows, and Singer 
- Experience writing production code for automated models, especially for Enterprise Data Models in Enterprise Data Platforms
- Experience with  Sisense for Cloud Data Teams (formerly known as Periscope), AWS Redshift, Superset, JupyterHub, Sagemaker, Athena, Redash, Google Suite, Anaconda-Navigator, Docker, GitHub, and Visual Studio Code

What’s unique about VGS:
- We’re a quickly scaling company with a startup mindset.
- We love to empower our people to take ownership! You’ll find you are given the freedom and will own the responsibility to be successful here. 
- We’re creating a remote-first philosophy. You’ll have a strong impact on a new cultural shift within the company.

What you get from us: 
- Competitive health benefits
- Flexible work hours and flexible PTO
- VGS stock options