Data Engineer

Job Description

Design, build, and maintain enterprise data quality frameworks, monitoring solutions, and automated validation processes to ensure trusted and reliable data across the organization. Develop and optimize ETL/ELT pipelines using Databricks, Spark, Python, SQL, and ADF while embedding data quality controls throughout the data lifecycle. Partner closely with Data Engineering, Governance, Analytics, and business teams to establish data quality standards, investigate and resolve data issues through root cause analysis, and deliver scalable technical solutions. Support CI/CD deployment processes, automated testing frameworks, cloud modernization initiatives, and present data quality findings and recommendations to both technical and business stakeholders.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

5+ years of experience in Data Engineering, Data Quality Engineering, or related roles.

Strong hands-on expertise with SQL, Python, Databricks, Spark, Azure Data Factory (ADF), Oracle, and cloud data platforms.

Experience building and supporting enterprise data quality frameworks, controls, monitoring, and validation processes.

Experience developing and optimizing ETL/ELT pipelines and embedding data quality checks into data workflows.

Knowledge of Git, CI/CD pipelines, automated testing, and DevOps best practices.

Strong analytical, troubleshooting, and root cause analysis skills.

Ability to collaborate with technical and business stakeholders and communicate findings effectively.

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.