Data Analytics & Engineering ConsultantLocation: New York City, NY (Hybrid)Duration: 6 to 12 Months Contract RolesRole OverviewThe CAD Data Analytics Program relies on skilled contingent resources to extend the team's capacity to deliver high-quality, data-driven insights that support client's Internal Audit function. This consultant role requires expertise in data engineering, ETL/ELT development, SQL, and Tableau dashboard development, and will operate as both a Subject Matter Expert and execution-focused resource working under the direction of the CAD Data team.Job Function and Key ResponsibilitiesWork primarily under the direction of the CAD Data team, with interaction with Internal Audit teams focused and purposeful, occurring when clarification is needed on requirements submitted through the CAD data intake form, or when presenting Tableau dashboard designs for user review and agreement prior to finalization.Design and build data pipelines and ETL/ELT processes to source, extract, and prepare data from Redshift, the company's data lake, in fulfillment of data intake requests received from Internal Audit, ranging from targeted population file pulls to more complex analytical datasets.Build, test, modify, and finalize Tableau dashboards in accordance with specifications provided by the CAD Data team, ensuring accuracy, completeness, and design quality prior to production release.Refresh and maintain dashboards according to their established schedules, utilizing Tableau Prep, Python, and StoneBranch for automation, with familiarity in Databricks as the team transitions its automation workflows.Configure subscription and alert notifications for Tableau dashboards when requested, and serve as the central recipient of all system-generated alerts to monitor and verify that CAD's alert inventory is functioning as intended.Support ongoing program administration, including maintaining CAD's dashboard inventory on a daily basis and updating CAD's Tableau Landing Page weekly to reflect current dashboard links and purposes.MUST HAVE QualificationsExperience in data engineering practices including the design and development of data pipelines and ETL/ELT processesProficiency in SQL for querying (building from scratch) using TOAD and extracting data from structured tables in Redshift.Proficiency in Tableau for dashboard development, modification, and maintenance.Experience with Tableau Prep for automated data preparation and refresh workflowsProficiency in Python for automation and data processingExperience with StoneBranch for workflow automation and schedulingProficiency in Databricks, including its GenAI capabilities, for data access, processing, and automation.Proficiency in Microsoft Excel: building macros (preferred), joining files, vetting files, teaching formulas to auditors, pivot tables, vlookups.