Sr. Data ScientistWashington DC (Day1 onsite)The pay range for this role is $90k - $110k per annum including any bonuses or variable pay.Key ResponsibilitiesDesign, develop, and maintain scalable data pipelines using Azure Databricks and Apache SparkImplement complex data transformations using Spark SQL and Python (mandatory)Build and manage analytics models using DBT Core / DBT Cloud, following analytics engineering best practicesDevelop and orchestrate data ingestion and transformation workflows using Azure Data FactoryEnsure data quality, reliability, and performance across batch and near real time pipelinesIntegrate Databricks workloads with downstream reporting, analytics, and AI/ML use casesCollaborate with cross functional teams to understand business requirements and translate them into technical solutionsImplement CI/CD pipelines and source control using Azure DevOpsApply secure data engineering practices aligned with WBG data governance and compliance standardsLeverage AI assisted tools to improve developer productivity, code quality, and operational efficiencyParticipate in design reviews, code reviews, and knowledge sharing sessionsMandatory Skills & QualificationsStrong expertise in Spark SQL and Python programming (Mandatory)Azure Databricks Data Engineer with at least one real time project implementationHands on experience with DBT Core and/or DBT CloudExperience building and managing pipelines using Azure Data FactoryProficiency with Azure DevOps (Repos, Pipelines, CI/CD)Experience using AI tools (e.g., AI assisted development, data analysis, or automation tools)Solid understanding of data warehousing concepts, ETL/ELT patterns, and distributed data processingAbility to work in agile delivery models and collaborate with global teamsPrimarily Looking AtAzure Data Factory (ADF)DBT CloudDatabricksPythonPreferred / Good to Have SkillsDatabricks Certification - Associate or Professional (strongly preferred)Experience with Azure data ecosystem (ADLS Gen2, Azure SQL, Synapse as applicable)Exposure to data governance, metadata management, and security frameworksFamiliarity with performance tuning and cost optimization on Databricks