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.

Development experience with Python and the pandas module.
Development experience with SQL and relational databases.
Experience in data migration, ETL processes, process scripting, and automation.
Understanding of system design and analysis.
A creative approach to problem-solving and learning, and an enjoyment of solving puzzles.

Data Conversion Engineer

Key skills