Data QA Specialist

Data QA SpecialistMiejsce pracy: WarszawaTechnologies we useExpectedSQLETLELTRedshiftBigQuerySnowflakeOptionalMicrosoft Power BILookerTableauGitAbout the projectWe’re looking for a Data QA Specialist to own the quality of our clickstream and web analytics data (Snowplow and related tracking), and the reporting pipelines that depend on it.You’ll sit between Analytics and Data Engineering, designing and running tests that ensure events are correctly tracked, transformed, and made available in our data warehouse and BI tools. Your work underpins reliable reporting and experimentation across the business.Your responsibilitiesValidate Snowplow / clickstream events from collection through to warehouse and reporting layers.Check event schemas, properties, timestamps, user IDs, sessions, and attribution fields for accuracy and consistency.Monitor and flag issues such as:Missing or duplicate eventsUnexpected spikes/dropsSchema drift / unannounced changesTest and validate ETL / ELT pipelines feeding dashboards and reporting tables (e.g. marketing, product, funnel performance).Compare source vs transformed data to ensure metrics (sessions, clicks, conversions, revenue, etc.) are accurate and reconciled.Help define data quality checks (row counts, null checks, referential integrity, thresholds, anomaly detection).Work with Analytics and Data Engineering to define:Test cases for new tracking requirements and eventsRegression tests when pipelines or schemas changeStaging and production environmentsUsing SQL queries, test scripts, and tool-based checksLog defects clearly and track them through to resolution.Act as the bridge between Analytics and Data Engineering:Translate analytics requirements into testable data conditions.Escalate issues with clear impact statements (“this breaks X dashboard / Y KPI”).Clarify and request access to tables, views, and logs needed for QA.Align on SLAs for data delivery and fixes.Coordinate with web / app teams where tracking implementation needs changes.Event schemas and naming conventionsKnown data caveats and limitationsTest plans and standard QA proceduresFlagging inconsistent naming or definitionsHelping enforce standards across teams.Our requirementsStrong experience in data quality / data QA / analytics engineering roles.Clickstream or web analytics data (e.g. Snowplow, GA, similar tools).SQL for investigation, reconciliation, and QA.Working with data warehouses / lakehouses (e.g. Redshift, BigQuery, Snowflake, etc.).Experience testing data pipelines (ETL/ELT) and reporting layers.Comfortable working with analytics teams (analysts / product analysts) and engineering / data engineering teams.Can explain data issues clearly to both technical and non-technical stakeholders.Can document data issues, risks, and decisions in a structured way.OptionalExposure to Snowplow in particular (event schemas, Iglu, enrichment, loaders).BI tools (e.g. Power BI, Looker, Tableau) – enough to validate metrics and reports.Data modelling or transformation frameworks (e.g. dbt).Data observability / quality tooling (e.g. Great Expectations, Monte Carlo, Soda, or similar).Version control (Git) and working with engineering-style workflows (PRs, code reviews).Understanding of web/app tracking implementations (tags, data layers, SDKs).This is how we organize our workThis is how we workat the client's siteSQUARE ONE RESOURCES sp. z o.o.At Square One Poland we link IT experts with the business. With over 25 years of experience, we specialize in recruitment processes on a global scale. Despite years of experience, we still have a startup DNA and this is our advantage. Our offices are located in London and Warsaw, however, we can reach clients from all over the world, from start-ups to big worldwide corporations.