Data Engineer

Kopius is a technology-driven company that specializes in digital strategy and engineering. They are seeking a Data Engineer to join their analytics and data engineering team, focusing on building and maintaining scalable enterprise data platforms, including ETL development and cloud-based solutions.

Responsibilities:

• Design, develop, and maintain enterprise data warehouse solutions supporting business operations and analytics initiatives
• Build and optimize ETL pipelines and data transformation processes across multiple data sources and platforms
• Develop scalable data models, including dimensional models and Kimball-based star schemas
• Contribute to the evolution and modernization of the enterprise data platform leveraging Azure cloud technologies
• Collaborate with engineering and analytics teams to improve data accessibility, reliability, and performance
• Support integration of new systems and data sources into the cloud-based analytics ecosystem
• Work extensively with Microsoft SQL Server, Azure cloud resources, and modern data engineering technologies
• Develop and maintain cloud-based data solutions leveraging Azure services and enterprise data platforms
• Ensure strong integration between analytics systems, cloud infrastructure, and reporting platforms
• Support data architecture initiatives focused on scalability, governance, and operational efficiency
• Contribute to the implementation of modern data engineering best practices and platform standards
• Develop and maintain relational and dimensional data models to support reporting and analytics use cases
• Partner with data analysts and stakeholders to identify, structure, and optimize available data sources
• Support Business Intelligence initiatives and reporting platforms such as Power BI and SSRS
• Work with structured, semi-structured, and unstructured data formats including JSON-based datasets
• Help improve data quality, consistency, and transformation processes across the analytics platform
• Support agile data engineering practices including CI/CD pipelines, backlog management, and incremental delivery
• Identify opportunities for process automation and platform optimization
• Contribute to continuous improvements in data platform scalability, maintainability, and operational efficiency
• Collaborate across teams to deliver high-quality solutions aligned with business priorities
• Participate in technical discussions, troubleshooting, and solution design initiatives

Requirements:

• Intermediate/Advanced English skills with strong communication abilities
• Self-motivated, proactive, and comfortable operating in collaborative, fast-paced environments
• Excellent analytical, troubleshooting, and problem-solving skills
• Strong attention to detail and ability to independently deliver technical solutions
• Excellent interpersonal, collaboration, and organizational skills
• 2+ years of hands-on experience in Data Engineering, ETL development, or Business Intelligence
• Strong experience with Microsoft SQL Server (2016+)
• Strong experience with SQL Server Integration Services (SSIS)
• Strong experience with ETL development and Transact-SQL
• Strong experience with Relational and dimensional data modeling
• Strong experience with Kimball Data Warehousing methodologies
• Experience with Microsoft Azure cloud platform and Azure resources
• Familiarity with Business Intelligence and reporting tools such as Power BI and SSRS
• Familiarity with JSON and semi-structured/unstructured data formats
• Familiarity with Modern data transformation techniques and cleansing methodologies
• Experience working with agile methodologies and modern engineering practices
• Strong understanding of enterprise data warehouse concepts and analytics platforms
• Familiarity with Spark SQL, Python, or C#
• Experience with NoSQL or non-relational databases, including Azure blob storage and Azure file tables
• Exposure to CI/CD pipelines and modern data platform automation practices
• Experience operating within cloud-based analytics and enterprise data ecosystems
• Experience within insurance, financial services, or digital business environments is a plus
• Relevant cloud or data engineering certifications are a plus