Data Engineer

Turnberry Solutions is a consulting firm that focuses on digital modernization, combining technology and strategy to enhance digital experiences. The Data Engineer will be responsible for designing and supporting data, analytics, and AI environments, as well as building and maintaining data pipelines across cloud platforms like Google Cloud and Microsoft Azure.

Responsibilities:

• Contribute to the design, configuration, and support of data, analytics, and AI environments across Google Cloud Platform (GCP) and Microsoft Azure, including Microsoft Fabric
• Build and maintain data pipelines to ingest, cleanse, transform, and curate structured and unstructured data
• Support batch and near–real-time data ingestion and transformation workflows
• Use Infrastructure as Code (IaC) tools (e.g., Terraform) to help automate cloud environment provisioning and configuration
• Configure and support cloud services related to data ingestion, integration, messaging, CI/CD, and data processing
• Assist with data modeling and performance optimization in cloud data warehouses (e.g., partitioning and clustering in BigQuery)
• Support the setup and tuning of operational databases or data-serving layers based on defined use cases
• Implement and maintain monitoring, logging, and alerting for data pipelines and platforms
• Write and maintain data transformations using SQL and Python
• Collaborate with engineers, analysts, and product teams in an iterative, product-focused environment
• Assemble large, complex data sets that meet functional/non-functional business requirements
• Write and troubleshoot SQL queries for data mining
• Perform complex data analysis and investigation for customer requests to explain results and to make appropriate recommendations
• Understand ETL that will aid in verification and testing of data
• Build processes supporting data transformation, data structures, metadata, dependency and workload management
• Successful history of manipulating, processing, and extracting value from large disconnected datasets
• Analyze business objectives and develop data solutions to meet customer needs
• Improve and customize current data solutions to meet business functional and non-functional requirements
• Research new and existing data sources in order to contribute to new development, improve data management processes, and make recommendations for data quality initiatives
• Perform periodic data quality reviews for internal and external data
• Ensure timely resolution of queries and data issues
• Look for new ways to find and collect data by researching potential new sources of information
• Work with data and analytics experts to strive for greater functionality in our data systems

Requirements:

• Demonstrated ability to analyze and profile data as a means to address various business problems through leveraging advanced data modeling, source system databases, or data mining techniques
• May provide consultative services to departments/divisions and committees
• Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement methods, and analytical tools and methodologies (e.g. data analysis, data profiling, modeling, etc.)
• Ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes
• Interpersonal skills and time management skills
• Strong analytical skills and the ability to identify and recommend solutions, advanced computer application skills, and a commitment to customer service
• Experience with data analysis, quality, and profiling; including data exploration tools including but not limited to Rapid SQL, AQT, Information Analyzer, and Informatics
• Strong knowledge of SQL required
• Ability to identify sets and subsets of information across multiple joins or unions of tables is preferred
• Strong understanding of data modeling concepts
• Problem solver with the initiative to think critically to identify improvement opportunities (error detection, error correction, root cause analysis)
• Education Bachelor's degree in Computer Science or Engineering from an accredited University or College OR Associate's degree in Computer Science or Engineering from an accredited University or College with two (2) years of experience