Data Engineer - ML & AI

As an Azure Data Engineer at the company, your role will involve developing and maintaining the Azure Databricks hosted data lake. This includes creating pipelines to connect extensive internal and external data sources, as well as writing APIs. You will be responsible for converting unprocessed data into easy-to-use tables for data analysts through ETL processes. Additionally, you will play a key role in promoting best practices and setting up standardized, effective processes to enhance your own work and that of the team. Key Responsibilities: - Develop and maintain the Azure Databricks hosted data lake by creating pipelines to extensive internal and external data sources, including writing APIs. - Convert unprocessed data into mastered, easy-to-use tables for data analysts through ETL. - Promote best practices and help set up standardized, effective processes to improve your work and work of the team. - Work collaboratively with the data engineering team to envision and layout the roadmap for the architecture of the data lake. - Drive data governance with high standards of quality. - Coordinate with the wider data and analytics team to ensure that the output meets the requirements of data science, reporting, and data analysis workstreams. - Contribute to driving the strong data culture behind ION Analytics digital transformation. - Actively build in-depth knowledge in various domains such as commercial, accounting, markets, content, product front end, and product back end. Qualifications Required: - Working knowledge of Machine Learning (ML) or Artificial Intelligence (AI) preferred. - Proficiency in Python and SQL, with experience in Pyspark considered a plus. - Experience with Azure and Databricks. - Experience with version control in Azure DevOps or GitHub. - Familiarity with agile software development methodologies (Scrum, Kanban, etc.). - Strong analytical and problem-solving skills. - Strong written and verbal communication skills. - Proactive team player with attention to detail and quality consciousness. - Ability to work to deadlines and manage expectations. Please note that no additional details about the company were provided in the job description. As an Azure Data Engineer at the company, your role will involve developing and maintaining the Azure Databricks hosted data lake. This includes creating pipelines to connect extensive internal and external data sources, as well as writing APIs. You will be responsible for converting unprocessed data into easy-to-use tables for data analysts through ETL processes. Additionally, you will play a key role in promoting best practices and setting up standardized, effective processes to enhance your own work and that of the team. Key Responsibilities: - Develop and maintain the Azure Databricks hosted data lake by creating pipelines to extensive internal and external data sources, including writing APIs. - Convert unprocessed data into mastered, easy-to-use tables for data analysts through ETL. - Promote best practices and help set up standardized, effective processes to improve your work and work of the team. - Work collaboratively with the data engineering team to envision and layout the roadmap for the architecture of the data lake. - Drive data governance with high standards of quality. - Coordinate with the wider data and analytics team to ensure that the output meets the requirements of data science, reporting, and data analysis workstreams. - Contribute to driving the strong data culture behind ION Analytics digital transformation. - Actively build in-depth knowledge in various domains such as commercial, accounting, markets, content, product front end, and product back end. Qualifications Required: - Working knowledge of Machine Learning (ML) or Artificial Intelligence (AI) preferred. - Proficiency in Python and SQL, with experience in Pyspark considered a plus. - Experience with Azure and Databricks. - Experience with version control in Azure DevOps or GitHub. - Familiarity with agile software development methodologies (Scrum, Kanban, etc.). - Strong analytical and problem-solving skills. - Strong written and verbal communication skills. - Proactive team player with attention to detail and quality consciousness. - Ability to work to deadlines and manage expectations. Please note that no additional details about the company were provided in the job description.