Technical Business Analyst / Data Analyst

As a Technical Business Analyst/Data Analyst in the Data Platform team, your role will involve bridging business requirements with data engineering on a large-scale data platform using Azure and Databricks technologies. You will be collaborating closely with engineering teams to ensure the successful implementation of data pipelines. Key Responsibilities: - Understand business needs and translate them into clear data and system requirements. - Define the required data, its sources, and the necessary structure. - Develop and maintain data models including tables, fields, and relationships. - Create data mappings from source to target and establish transformation rules. - Collaborate with engineering teams to ensure the adherence of data pipelines to requirements. - Validate outputs to ensure data accuracy, completeness, and consistency. - Identify gaps, dependencies, and facilitate alignment across different teams. - Support testing activities such as User Acceptance Testing (UAT) and Quality Assurance Testing (QAT) to ensure smooth delivery across releases. Required Skills: - 37 years of experience as a Business Analyst in data/technology projects. - Proficiency in data modeling including schema design, table structures, and relationships. - Strong working knowledge of SQL for data analysis and validation. - Hands-on experience working with Databricks for data analysis, validation, and understanding of pipelines. - Good understanding of the Azure data ecosystem, with a focus on Azure Data Lake Storage (ADLS) and Azure Data Factory (ADF). - Familiarity with data pipelines and ETL processes. - Ability to collaborate effectively with data engineering teams. - Strong communication and documentation skills. Good to Have: - Exposure to Kafka and streaming data pipelines. - Experience with API-based data ingestion. - Prior experience in healthcare data management, specifically claims, member, and provider data. Please note that candidates lacking hands-on experience in data modeling, SQL, and working on Azure/Databricks-based data platforms may not be suitable for this role. As a Technical Business Analyst/Data Analyst in the Data Platform team, your role will involve bridging business requirements with data engineering on a large-scale data platform using Azure and Databricks technologies. You will be collaborating closely with engineering teams to ensure the successful implementation of data pipelines. Key Responsibilities: - Understand business needs and translate them into clear data and system requirements. - Define the required data, its sources, and the necessary structure. - Develop and maintain data models including tables, fields, and relationships. - Create data mappings from source to target and establish transformation rules. - Collaborate with engineering teams to ensure the adherence of data pipelines to requirements. - Validate outputs to ensure data accuracy, completeness, and consistency. - Identify gaps, dependencies, and facilitate alignment across different teams. - Support testing activities such as User Acceptance Testing (UAT) and Quality Assurance Testing (QAT) to ensure smooth delivery across releases. Required Skills: - 37 years of experience as a Business Analyst in data/technology projects. - Proficiency in data modeling including schema design, table structures, and relationships. - Strong working knowledge of SQL for data analysis and validation. - Hands-on experience working with Databricks for data analysis, validation, and understanding of pipelines. - Good understanding of the Azure data ecosystem, with a focus on Azure Data Lake Storage (ADLS) and Azure Data Factory (ADF). - Familiarity with data pipelines and ETL processes. - Ability to collaborate effectively with data engineering teams. - Strong communication and documentation skills. Good to Have: - Exposure to Kafka and streaming data pipelines. - Experience with API-based data ingestion. - Prior experience in healthcare data management, specifically claims, member, and provider data. Please note that candidates lacking hands-on experience in data modeling, SQL, and working on Azure/Databricks-based data platforms may not be suitable for this role.