Develop an understanding of the data environment through profiling and analysis to enhance data quality.
Build Python-based solutions for data extraction, cleansing, transformation, and validation to support data migration.
Document data integration processes, ensure traceability and develop data monitoring solutions.
Collaborate with architects for solution integration ensuring alignment with company standards.
Manage data tools and platforms for proper software/infrastructure updates.
Work with the Data Management Organization to align with data quality improvement objectives.
Ensure solutions meet Service Level Agreements with capacity and performance considerations.

Requirements

Bachelor’s Degree in Computer Science or equivalent experience preferred.
4 years of experience in software engineering with a strong focus on Python and data engineering.
Advanced proficiency in Python and **Agent Development **with strong problem-solving skills required.
3 years of development experience and proficiency with Relational Databases, NoSQL, and/or Data Lakehouses (**Snowflake**, Microsoft Fabric, Databricks)
Intermediate proficiency in cloud technologies, including **Google Cloud Platform**, required.
Working knowledge of REST standards preferred.
Experienced in data quality, data integration, and data processing.
Proficiency with data movement solutions like Informatica IICS, Fivetran, and Airbyte.
Experience with data transformation solutions, such as dbt.
Experience with workflow orchestration tools such as **Airflow or Astronmer**, Dagster, and Prefect.
Familiarity with CI/CD and container technology is preferred. Understanding usage of AI technologies for development and proficiency in prompting

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Pythondata extractiondata cleansingdata transformationdata validationRelational DatabasesNoSQLData Lakehousesdata qualitydata integration

problem-solvingcollaborationdocumentation