Azure Databricks DeveloperLocation: Louisville, KY & Pittsburgh, PA – 100% Onsite Long Term Contract – W2/ C2CInterview Mode: Face-to-Face (F2F) – Final Round Note: Locals Only – No relocation or remote optionsJob Description:We are seeking a highly skilled Azure Databricks Developer to join our team for an onsite role requiring in-person interviews. The ideal candidate will have strong hands-on experience working with Azure Data Services, especially Databricks, and should be comfortable working directly from the client location.Key Responsibilities:Design, develop, and optimize data pipelines using Azure Databricks and Apache SparkBuild scalable ETL/ELT processes to ingest data from various sources (structured, semi-structured)Work closely with data architects and analysts to understand data requirements and implement solutionsWrite advanced PySpark/Scala scripts and performance-tune Spark jobsImplement data quality checks and validation rulesIntegrate with Azure components like Data Lake Storage (ADLS), Data Factory, Synapse, Event HubsSupport deployment, monitoring, and debugging in Azure environmentsCollaborate in Agile/Scrum teams, attend stand-ups, demos, and code reviewsRequired Skills:8+ years of experience in Data Engineering roles5-7+ years of strong hands-on experience with Azure DatabricksStrong knowledge of PySpark, SQL, Spark SQLExperience with Azure Data Factory, ADLS Gen2, Synapse Analytics, and Azure DevOpsProficiency in working with Delta Lake, DataFrames, and optimization techniquesExcellent understanding of data modeling and large-scale data processingStrong debugging, performance tuning, and troubleshooting skillsAbility to work onsite and attend face-to-face interviewsNice to Have:Experience with Power BI, Azure ML, or Real-time streaming (Event Hubs/Kafka)Knowledge of CI/CD pipelines and automation using Azure DevOps
Azure Databricks Developer ___ Louisville, KY & Pittsburgh, PA (Onsite) ___ Contract in pittsburgh at Unknown Company
This position is listed as contract and able to be worked remotely.