Data Engineering Consultant

Primary Responsibilities:Design, develop, and implement scalable data pipelines using Azure DatabricksDevelop PySpark-based data transformations and integrate structured and unstructured data from various sourcesOptimize Databricks clusters for performance, scalability, and cost-efficiency within the Azure ecosystemMonitor, troubleshoot, and resolve performance bottlenecks in Databricks workloadsManage orchestration and scheduling of end to end data pipeline using tool like Apache airflow, ADF scheduling, logic apps Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do soQualifications - ExternalRequired Qualifications:Undergraduate degree or equivalent experience7+ years of experience in IT industry and 6+ years of experience in data engineering with 3+ years of hands-on experience in Azure DatabricksProficiency in PySpark, Python and SQL for data processing in DatabricksProven solid expertise in the Azure ecosystem, including Azure Synapse, Azure SQL, ADLS, and Azure Functions