A leading data solutions provider in the United States is looking for a Data Engineer to modernize and optimize legacy data processes. The ideal candidate will perform SAS Data Quality conversion tasks, write and optimize SQL queries, and collaborate with stakeholders to deliver reliable data pipelines. Proficiency in SQL and experience with data quality tools are essential. Join a dynamic team focused on data governance and quality initiatives.
Qualifications
Proficient in SQL with practical experience translating between SQL dialects.
Experience with SAS Data Quality tools.
Understanding of ETL concepts and data pipeline development.
Responsibilities
Perform SAS Data Quality conversion tasks.
Write and optimize SQL queries across multiple dialects.
Collaborate on data requirements and deliver data pipelines.
Skills
SQL proficiency
SAS Data Quality tools
ETL concepts
Problem-solving skills
Collaboration
Tools
Teradata SQL
PostgreSQL
MySQL
Microsoft SQL Server
Python
Job description
Key Responsibilities
Perform SAS Data Quality (DQ) conversion tasks to modernize and optimize legacy data processes.
Write, optimize, and translate complex SQL queries across multiple SQL dialects, with an emphasis on Teradata and SAS SQL.
Collaborate with data architects, analysts, and business stakeholders to understand data requirements and deliver reliable data pipelines.
Assist in data integration, transformation, and migration efforts across platforms.
Monitor and troubleshoot ETL jobs and data workflows to ensure data accuracy and reliability.
Participate in code reviews, testing, and documentation to maintain high-quality standards.
Support data governance and quality initiatives as part of the data engineering team.
Must-Have Skills
Proficient in SQL with practical experience translating between two or more SQL dialects.
Experience with SAS Data Quality (DQ) tools and/or SAS data processing.
Working knowledge of Teradata SQL dialect preferred.
Understanding of ETL concepts and data pipeline development.
Strong problem‑solving skills and attention to detail.
Ability to work collaboratively in a team and communicate effectively with technical and non‑technical stakeholders.
Good‑to‑Have Skills
Prior experience in data warehousing and large‑scale data environments.
Familiarity with other SQL dialects such as PostgreSQL, MySQL, or Microsoft SQL Server.
Basic knowledge of Python or other scripting languages used for data engineering.
Exposure to cloud platforms (AWS) and cloud‑based data services.
Understanding of data governance, data quality frameworks, and best practices.