Position Overview

We are seeking a hands-on Data Engineer to design, build, and optimize our data pipeline and reporting infrastructure. This role will focus on ETLing data from our low-code platform into a SQL-based data warehouse, merging production and archived historical data, and preparing high-quality, performant datasets for client reporting.

The ideal candidate has strong experience in Python-based ETL development, SQL data modeling, performance optimization, and Power BI administration and report development. This is a contract-to-hire position with the opportunity to transition into a long-term role.

Key Responsibilities

Data Engineering & ETL

• Design and implement ETL processes to extract data from a low-code platform into a SQL database.
• Merge production and archived historical data into unified reporting tables.
• Develop Python scripts to handle large-volume tables, including:
  • Incremental loads
  • Create and update (upsert) logic
  • Change detection
  • Error handling and logging
• Ensure data integrity, consistency, and reliability across all pipelines.
• Automate data workflows and monitor for failures or performance degradation.

Data Warehouse & Modeling

• Design and maintain a reporting-ready SQL data warehouse.
• Develop efficient data models (fact/dimension schemas where appropriate).
• Implement best practices for:
  • Referential integrity
  • Indexing strategies
  • Partitioning (where applicable)
  • Query performance optimization
• Ensure scalability as data volumes grow.

Reporting & Power BI

• Prepare curated datasets optimized for reporting and analytics.
• Administer Power BI workspace environments.
• Build and maintain Power BI reports and dashboards for client-facing use.