Ohio Staffing
Data Engineer III - Databricks
The Data Engineer III - Databricks is responsible for engineering, architecting, developing, and implementing unique and innovative enterprise-wide solutions. Essential functions include driving the cloud solution utilizing Azure DevOps Databricks, contributing to data stewardship workgroups and teams in data management and governance activities, and championing metadata and data quality practices across the organization. The role involves understanding stakeholder business culture and priorities, performing analysis and research to support glossary definitions, policies, programs, standards, guidelines, and workflows, leading the development and maintenance of metadata catalogs, identifying and quantifying data related pain points, collaborating with SMEs to develop business rules, and quantifying and qualifying reported data quality issues. The position requires setting objectives, contributing to operational area goals, and working independently with discretion within established operational boundaries. The role also involves performing any other job duties as requested. The candidate must have a Bachelor's degree in Computer Science or a related field or equivalent years of relevant work experience. A minimum of three years of healthcare payer experience and five years of experience designing and developing ETL solutions is required. Demonstrable experience in all stages of definition, design, implementation, testing, and deployment of complex database, ETL, BI, and analytical solutions is necessary. Participation and experience working within a formal Data Warehouse and Governance environment is preferred. Understanding of Data Vault and Kimball model and healthcare domain knowledge is also required. Experience with Databricks, Python, PySpark, and Azure Data Factory is essential. Competencies include proven ability to write complex queries, developing medium to complex data quality profiling or metadata analysis processes, managing multiple medium to large scale projects, understanding data management and governance concepts, establishing effective working relationships, strong problem-solving skills, and excellent written and verbal communication skills.
The Data Engineer III - Databricks is responsible for engineering, architecting, developing, and implementing unique and innovative enterprise-wide solutions. Essential functions include driving the cloud solution utilizing Azure DevOps Databricks, contributing to data stewardship workgroups and teams in data management and governance activities, and championing metadata and data quality practices across the organization. The role involves understanding stakeholder business culture and priorities, performing analysis and research to support glossary definitions, policies, programs, standards, guidelines, and workflows, leading the development and maintenance of metadata catalogs, identifying and quantifying data related pain points, collaborating with SMEs to develop business rules, and quantifying and qualifying reported data quality issues. The position requires setting objectives, contributing to operational area goals, and working independently with discretion within established operational boundaries. The role also involves performing any other job duties as requested. The candidate must have a Bachelor's degree in Computer Science or a related field or equivalent years of relevant work experience. A minimum of three years of healthcare payer experience and five years of experience designing and developing ETL solutions is required. Demonstrable experience in all stages of definition, design, implementation, testing, and deployment of complex database, ETL, BI, and analytical solutions is necessary. Participation and experience working within a formal Data Warehouse and Governance environment is preferred. Understanding of Data Vault and Kimball model and healthcare domain knowledge is also required. Experience with Databricks, Python, PySpark, and Azure Data Factory is essential. Competencies include proven ability to write complex queries, developing medium to complex data quality profiling or metadata analysis processes, managing multiple medium to large scale projects, understanding data management and governance concepts, establishing effective working relationships, strong problem-solving skills, and excellent written and verbal communication skills.