Data Conversion Engineer

CanadaRemoteFull-time

AI Summary

Supports migration of utility billing data from legacy systems into a modern platform by building and maintaining ETL scripts, auditing data quality, and profiling source schemas. Collaborates with the data conversion and client experience teams.

About this role

The Company

2025 Deloitte Technology Fast 50 Canada Recipient & Fast 500 North America Recipient 🏆

SpryPoint is modernizing how utilities serve their communities. As a high-growth software company, we're shaking up the status quo in the utility industry with the first and only truly cloud-native customer service and operations platform purpose-built for modern utilities.

Founded by industry veterans in 2011, we've grown from a profitable startup to a rapidly scaling company of 300+ employees serving 100+ utility clients across North America and the Caribbean. Our mission is simple: utility leaders should expect more from their technology providers.

Utilities face urgent demand to replace inefficient legacy systems while managing increasing operational complexity, and evolving customer expectations. With more than a decade of experience, and a track record of successful implementations spanning water, electric, and gas utilities, SpryPoint has built a reputation as a trusted and mission-critical partner to utilities across North America.

We deliver comprehensive solutions including SpryCIS, SpryEngage, SpryMobile, and SpryWallet that modernize the entire meter-to-cash process. What sets us apart? Our "updates, not upgrades" approach, user-centric design, and unwavering focus on customer success.

Backed by strategic investment from Norwest Venture Partners since 2023, and an exciting new investment partnership from Insight Partners announced in 2026, we're accelerating our growth while staying true to our core values: lead with kindness, vision with impact, radical honesty, bold disruption, keep it simple, and execute with excellence.

Join our award-winning team in transforming an essential industry that powers communities across the Americas.

Position Overview

As a Data Conversion Engineer at SpryPoint you will play a key role in supporting the transformation and migration of utility billing data from legacy systems into our modern utility and billing platform.

You will work in the Technical Services department alongside the rest of the Data Conversion team to extract, transform, and load (ETL) customer data, ensuring accuracy, efficiency, reliability, and quality. You will have opportunities to collaborate with pair programming, learn best practices in data migration, and contribute to process improvements.

This role is a great opportunity for someone early in their data engineering career who wants to build strong foundations in data transformation, conversion auditing, and process optimization within a collaborative and iterative environment.

Responsibilities

Lead and manage ETL migration processes across multiple concurrent projects, ensuring robust data pipeline development and timely project delivery.

Develop and maintain efficient extraction, transformation, and loading scripts, utilizing Python, SQL, and related data engineering tools to ensure high-quality data migrations.

Implement feedback-driven improvements from clients and internal teams, enhancing data conversion quality, performance, and reliability.

Actively contribute to data quality assurance processes and review datasets for accuracy, completeness, and consistency.

Conduct in-depth analysis and profiling of diverse source database schemas (including relational and non-relational legacy systems) to accurately map and facilitate successful data extraction and migration.

Collaborate closely with the broader Client Experience team to seamlessly integrate client data into SpryPoint products, enabling smooth and timely go-live processes.

Work with the Data Conversion team to establish and promote best practices, create documentation, and drive continuous improvement in data migration processes, automation, and observability.

Actively participate in daily standups and weekly review sessions, clearly communicating progress, raising blockers, and incorporating feedback to continuously improve data engineering tasks and processes.