Senior Data Engineer
Posted on 12/22/2023
INACTIVE
Procurify

51-200 employees

Intelligent spend management and procurement solution
Company Overview
Procurify stands out as a leader in Intelligent Spend Management, providing organizations with unparalleled visibility and control over their business expenses, which has led to significant time and cost savings. Their robust procure-to-pay solution, which integrates seamlessly with major ERP accounting systems, manages over US$30 billion of organizational spend, demonstrating their trustworthiness and industry leadership. The company's culture is centered around providing value to its customers, as evidenced by its recognition as the #1 Purchasing Leader by G2.
Data & Analytics

Company Stage

Series C

Total Funding

$82.2M

Founded

2013

Headquarters

Vancouver, Canada

Growth & Insights
Headcount

6 month growth

0%

1 year growth

-3%

2 year growth

33%
Locations
Remote
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
MySQL
NoSQL
Data Science
Apache Spark
SQL
Postgres
Tableau
Apache Hive
MongoDB
CategoriesNew
Data & Analytics
Requirements
  • 5+ years in a Software Engineer role, including 2+ years experience in a Data Engineer role
  • Expertise with building ETL/ELT tools, Data Lakehouse tech (Databricks, Photon, Apache Spark, Hive, Parquet), and Visualization Platforms (Tableau, Thoughtspot)
  • Experience with Databricks and its recent product suite (autoloader, DLT, DAB)
  • Experience developing in Python and pyspark
  • Knowledge of one or more data architectures and data modeling techniques
  • Advanced SQL knowledge and strong experience working with relational databases (PostgreSQL, MySQL) and NoSQL databases (dynamoDB, MongoDB)
  • Experience building data pipelines for both structured and unstructured data sources
  • Strong understanding of Data Science concepts
  • Familiar with DevOps principles such as design for manageability and root cause analysis
  • Familiar working within leading software development best practices such as scrum/kanban, CI/CD, and test automation
Responsibilities
  • Design, create, evolve, and maintain scalable and efficient data pipelines, dashboards, model deployment, and model monitoring frameworks
  • Manage ETL/ELT activities supporting workloads including ad-hoc analysis, visualizations, observability and operational monitoring, data privacy and security, data governance, etc.
  • Partner across Product and Engineering teams on new reporting and data requirements to create product capabilities that fundamentally rely on data models
  • Leverage experimental and ad-hoc data-driven models, prototypes, and visualizations for rapid feasibility assessment and product roadmap planning
  • Drive conversations within Engineering to improve and optimize the source data models, including those in our product platform
  • Identify, design, and implement internal process improvements, including automation for data quality control and data validation, improved data delivery, and scalability
  • Comfortable leading by example and using influence to drive collaboration, documentation, and knowledge sharing across teams and with a broad range of stakeholders
  • Actively mentoring and leveling up developers within the team you’re on and extending across engineering teams
  • Able to demonstrate initiative, work independently, and thrive with autonomy while collaborating across teams in a culture of priority setting and moving forward with urgency in alignment with our organizational strategy
  • Adept at focusing on multiple competing priorities, solving unique and complex technical problems, and persistently resolving blockers to progress
Desired Qualifications
  • Familiar with DevOps principles such as design for manageability and root cause analysis
  • Familiar working within leading software development best practices such as scrum/kanban, CI/CD, and test automation