Data Engineer

PayIt•Kansas City, MO

14h•$100,000 - $125,000•Hybrid

About The Position

In this position you will work closely with other Data Engineers on your team, and members of the broader Engineering organization, to ensure that the business has access to high quality, accurate data via multiple channels (reporting, data visualization tools, data warehouse, BI tools, etc). Other duties as necessary.

Requirements

Strong SQL experience and proven expertise handling large volumes of data, including data modeling with dbt
Expertise in Python with a working knowledge of test-driven development
Experience deploying software to public cloud infrastructure - AWS (preferred), GCP, Azure
Experience with RDBMS, NoSQL and Cloud data storage technologies - AWS DocumentDB, MongoDB, Postgres and Snowflake experience preferred
Experience with building ETL solutions and transforming data between different types of sources
Experience with modern, Python-based data orchestration tools like Dagster, Prefect or Airflow
Experience building solutions for analytical reporting and business intelligence
Experience with a data visualization tool such as Tableau, Apache Superset or Looker
Experience building or working on reconciliation systems that compare data from multiple sources for verification.
High integrity, drive, grit, high aptitude, and team orientation.
Collaborative and passionate about the work.
Ready to roll up their sleeves, solve problems, and find new opportunities to win with our clients.
High aptitude, high integrity people who are great communicators and want to be part of a growing team.

Nice To Haves

Experience working with large-scale distributed systems, developing real-time payments systems, and/or working with financial, accounting, or payments systems
Experience with CI/CD such as GitHub Actions or Jenkins
Experience working with data lakes and/or data warehouses
Experience with Docker and Kubernetes
Knowledge of microservices architectures

Responsibilities

Ensure that the business has access to high quality, accurate data via multiple channels (reporting, data visualization tools, data warehouse, BI tools, etc).
Building ETL solutions and transforming data between different types of sources.
Building solutions for analytical reporting and business intelligence.
Building or working on reconciliation systems that compare data from multiple sources for verification.
Develop software professionally following agile methodologies (e.g., Scrum, Kanban).