Job Opportunities API

WHY DEPT®? We are pioneers at heart. What this means, is that we are always leaning forward, thinking of what we can create tomorrow that does not exist today. We were born digital and we are a new model of agency, with a deep skillset in tech and marketing. That’s why we hire curious, self-driven, talented people who never stop innovating. Our culture is big enough to cope and small enough to care. Meaning, that with people across 20+ countries, we’re big enough to provide you with the best tools, global opportunities, and benefits that help you thrive. While acting small by investing in you, your growth, your team, and giving you the autonomy to solve our clients' problems, no matter where you are in the world.  This is a 3 month fixed term salaried contract, located in Ontario Canada. Preferably in Toronto. The Role: The Senior Data Analyst is a hands-on analytical contributor embedded in the engineering team. This role bridges the gap between the data itself and the engineers, product managers, and data analysts building and evaluating the Knowledge Graph. The primary focus is data integrity: validating datasets, verifying query outputs, tracing the root cause of discrepancies, and applying statistical methods to assess data quality across multiple storage technologies.   This is a practitioner role, not a consulting engagement. The deliverable is evidence — validated results, documented defects, root cause analysis, and statistical assessments that the team can act on.   What You’ll Do: Validate datasets loaded into each technology to confirm completeness, accuracy, and structural integrity relative to source data in Databricks and CDS  Verify benchmark query outputs across technologies — confirm that the same logical query against the same underlying data produces consistent, correct results regardless of which system executes it   Identify, document, and trace the root cause of data discrepancies and defects discovered during validation; distinguish between ETL issues, schema translation errors, technology-specific behavior, and upstream data quality problems   Develop and maintain validation test cases and expected outputs for benchmark queries and compliance use cases   Support the collection and documentation of compliance use cases from the business unit   Help assess each use case: can it be fulfilled by a conventional database approach, or does it require the traversal and pattern-matching capabilities of a purpose-built graph database?   Contribute analytical rigor to use case triage — this is a cost-and-complexity decision as much as a technical one   Apply statistical methods to evaluate dataset representativeness, sampling quality, and measurement reliability across benchmark runs   Analyze benchmark result distributions — identify outliers, assess variance across cold/warm/concurrent runs, and flag results that require deeper investigation before scoring   Produce summary statistics and data quality reports that inform the team's architecture assessment   Document validation findings, defect reports, and root cause analyses in a format the engineering team can act on Maintain a running record of known data issues and their resolution status across each technology under evaluation What You Bring: Demonstrated experience validating large, complex datasets — identifying discrepancies, tracing root causes, and documenting findings clearly Strong SQL skills; ability to write analytical queries against relational databases (PostgreSQL experience preferred) Experience working with data at significant scale — hundreds of millions of records — where manual spot-checking is insufficient and systematic validation approaches are required Familiarity with ETL pipelines and the ty