SAS DI Controls Analyst | IT Recruitment

  • Contract
  • Remote


  • 3-year diploma or higher in the related field of study


Experience Required

The SAS DI Controls Analyst is responsible for designing, developing, documenting, and implementing data quality checks across all data assets (ETL jobs, reports, dashboards, and data pipelines). The primary goal for this role is therefore to ensure high quality of data delivered to internal stakeholders and customers.

  • 5+ years of experience with SAS Data Management Studio/SAS Data Flux, SAS Enterprise Guide/SAS DI Studio.
  • 5+ years of programming experience.
  • Must have experience working in Medium to Large scale data quality environments.
  • Create High level, low-level, and detail technical design specifications for the Data Integration (SAS Data Management Studio).
  • Involved in Gathering and Analyzing Business Requirements, Logical Design and Physical Design of database migration data quality controls.
  • Performing programming activities including analysis, design, development, testing, and documentation of the data integrating solution.
  • Conduct detail source system analysis, data analysis and source to target data mapping.
  • Extract data from databases using SAS SQL procedures and write code to manipulate, aggregate and merge datasets.
  • Creating the Database Objects (Tables with Integrity Constraints, Indexes and Views).
  • Preparation of test strategy & Plans, developing test cases and data, Performing system and integration testing.
  • Demonstrated ability to translate and transform business requirements into data quality check/workflows.
  • Expertise in troubleshooting and debugging skills.
  • Must possess strong knowledge of relational database concepts.
  • Excellent analytical and communication skills required to effectively work in the field of applications development and maintenance.
  • Excellent at understanding integration technologies, domains, and workflows.



  • Gather, organize, and analyse data from various databases, source systems or external systems to profile, monitor and evaluate data quality.
  • Implement data quality workflows, mappings, mapplets, analyst profiles, scorecards and reference tables and automation thereof.
  • Develops data quality key performance indicators (KPI’s) and reporting to measure, monitor and evaluate data quality across the entire data stack.
  • Develop a DQ dashboard and mappings for business to track the quality of their data.
  • Track, monitor and document testing results post DQ rule set implementation.
  • Performs root cause analysis and collaborates with data stakeholders to identify and understand factors that contribute to data quality issues.
  • Recommends data capture and operational process improvements based on findings form RCA’s.
  • Coordinates with the appropriate internal (e.g., IT, Operations) and external stakeholders (e.g., technology or data partners) in the correction of source data or creation of translation sources, where applicable.
  • The development and maintenance of Extract Transform and Load (ETL) processes, database and performance administration, and dimensional design of the table structure
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