Addison Group
Title: QA Engineer
Location: Coppell, TX
Salary Range: $115K-$130K
We are looking to bring on a QA Engineer due to new growth within our organization. This person will need to bring 6+ years of QA Engineering experience to make an immediate impact to the new business initiatives we have laid out for the next year. The focus on this team though is to specialize in running the QA lifecycle and setting processes around their data environment. QA Engineering typically helps with automation/testing of operations or applications, this team is focusing on our data management on their metadata and enterprise reporting tools.
We will need someone with experience running full QA data lifecycles in enterprise environments, specifically working within Databricks and Azure. This will include data integrity, validation of data ingestion, transformation, and loading processes (ETL/ELT). They will also need experience in monitoring pipelines (SQL) to identify metadata data drifts, schema changes, and/or transformation issues. This team will also be engineering QA automation/testing around the enterprise reporting tools (Power BI) for the business as well. Governance and setting standardized process around our data best-practices will also be key.
Tools needed for this role will include Databricks (PySpark/Scala) for automation, CI/CD tools (ADO or Terraform), SQL/T-SQL, ETL testing, and working in a cloud environment (Azure or AWS). Any certifications or data architecture knowledge (data modeling, data warehousing, data design) is a plus.
Personality-wise we need someone who can work well within a team while also completing solo tasks assigned. Collaboration between functional and technical individuals will also be day-to-day on projects, so we need someone who can partner with all aspects of the business.
Top Skills:
6+ Years of Data QA Engineering
Databricks (PySpark, Spark, Scala)
QA automation/testing of data models and pipelines (ETL, ELT, data processing, etc.)
Cloud-based environments (Azure or AWS)
Data Pipeline Architecture and CI/CD methodology
SQL
Pluses:
Data Governance
Industry experience
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Location: Coppell, TX
Salary Range: $115K-$130K
We are looking to bring on a QA Engineer due to new growth within our organization. This person will need to bring 6+ years of QA Engineering experience to make an immediate impact to the new business initiatives we have laid out for the next year. The focus on this team though is to specialize in running the QA lifecycle and setting processes around their data environment. QA Engineering typically helps with automation/testing of operations or applications, this team is focusing on our data management on their metadata and enterprise reporting tools.
We will need someone with experience running full QA data lifecycles in enterprise environments, specifically working within Databricks and Azure. This will include data integrity, validation of data ingestion, transformation, and loading processes (ETL/ELT). They will also need experience in monitoring pipelines (SQL) to identify metadata data drifts, schema changes, and/or transformation issues. This team will also be engineering QA automation/testing around the enterprise reporting tools (Power BI) for the business as well. Governance and setting standardized process around our data best-practices will also be key.
Tools needed for this role will include Databricks (PySpark/Scala) for automation, CI/CD tools (ADO or Terraform), SQL/T-SQL, ETL testing, and working in a cloud environment (Azure or AWS). Any certifications or data architecture knowledge (data modeling, data warehousing, data design) is a plus.
Personality-wise we need someone who can work well within a team while also completing solo tasks assigned. Collaboration between functional and technical individuals will also be day-to-day on projects, so we need someone who can partner with all aspects of the business.
Top Skills:
6+ Years of Data QA Engineering
Databricks (PySpark, Spark, Scala)
QA automation/testing of data models and pipelines (ETL, ELT, data processing, etc.)
Cloud-based environments (Azure or AWS)
Data Pipeline Architecture and CI/CD methodology
SQL
Pluses:
Data Governance
Industry experience
#J-18808-Ljbffr