QA Engineer (Data & Analytics)

As a recruitment company, DCG understands that every business is powered by experienced professionals. Our management style and partnership approach enable us to meet your needs and provide continuous support. Due to our ongoing growth and the large number of recruitment projects we undertake for our partners, we are currently looking for:QA Engineer (Data & Analytics)We are looking for candidates who are available immediately, with a maximum notice period of two weeks.Responsibilities:Define and implement data quality validation strategies across pipelines, data lakes, and warehousesVerify data consistency, integrity, completeness, and transformations from source systems to downstream analytics platforms like ThoughtSpot and DatabricksDevelop and execute end-to-end data validation and reconciliation tests to ensure accurate reporting and insightsWork with engineers to implement data contracts, schema validations, and anomaly detection mechanisms using tools like Great ExpectationsPerform exploratory data testing, investigating discrepancies and ensuring data correctness across multiple environmentsValidate data migrations, ensuring business continuity and minimal disruption during cloud transitions (e.g. Databricks to GCP migration)Collaborate with data engineers, analysts, and software engineers to establish and enforce data quality standardsWork closely with teams to define data validation criteria, SLAs for data freshness, and monitoring strategiesParticipate in design and planning discussions to ensure data observability, lineage tracking, and governance are embedded earlyChampion best practices in data testing, monitoring, and alerting, ensuring quick detection and resolution of data quality issuesLeverage data quality metrics to identify trends, gaps, and areas for improvementExplore and advocate for new tools, frameworks, and methodologies to enhance data testing efficiencySupport data performance testing by validating query performance, scalability, and system reliabilityAssist with data security, compliance, and privacy testing, ensuring alignment with regulatory and organisational standards Requirements:Proven experience in QA for data projects, with a focus on data validation, pipelines, and analytics testingStrong understanding of data engineering workflows, ETL processes, and data lake architecturesExperience testing data transformations, APIs, and integrations in cloud-based environments (AWS, GCP, or Azure)Familiarity with data quality frameworks like Great Expectations or similar toolsHands-on experience working with SQL for data validation and reconciliationKnowledge of BI and analytics tools (e.g. ThoughtSpot, Power BI, Looker, Tableau) and how to validate reportsExcellent communication skills, with the ability to collaborate and advocate for quality across teamsDetail-oriented, analytical, and proactive, with a passion for data quality and accuracyA natural problem solver who is able to investigate data issues and drive resolutionsStrong collaborator and communicator, bridging gaps between QA, engineering, and data teamsAdaptable and curious, keen to explore emerging data quality trends and best practicesKnowledge of English at B2 level (minimum)Nice to have:Experience in testing large-scale data migrations (e.g. Databricks to GCP)Understanding of data observability, lineage tracking, and monitoring toolsExperience with performance testing for data platforms (query performance, scalability)Awareness of data security and governance best practicesKnowledge of machine learning model validation and AI testing Offer:Private medical careCo-financing for the sports cardTraining & learning opportunitiesConstant support of dedicated consultantEmployee referral program