Responsibilities We are seeking a highly skilled Senior Data Engineer to join a newly formed team focused on delivering cutting-edge, data-driven products. This role will be pivotal in designing and implementing robust data pipelines, managing both structured and unstructured data, and ensuring the seamless execution of end-to-end data solutions. The ideal candidate will possess deep expertise in data engineering and advanced analytics. Accountabilities: Design, develop, maintain, and document data pipelines (cleansing, blending, migration, transformation), run books, and data storage systems. Design, develop, maintain, and document data models based on requirements. Assist with the maintenance of existing models, data systems and platforms. Gather and analyze requirements, developing data processes and applications that meet our business needs. Challenge the status quo and identify new opportunities for data acquisition and transformation. Ignite positive change by assisting team members and Line of Business teams with the utilization of new data assets. Collaborate with members of the Data Engineering team to support internal clients such as Data Scientists, Visualization Specialists, various Line of Business teams with their various data needs. Collaborate with product manager and product owner teams review and refine functional and non-functional requirements. Collaborate with Platform R&D teams to ensure smooth and reliable integration. Drive innovation by keeping current on relevant data trends via researching, presenting, and accurately articulating the benefits and goals of data architecture related technologies, such as Big Data, Hadoop, NoSQL, Cloud. Collaborate between highly distributed data engineering team's members as well as project management, development, and architecture teams. Required Skills and Experience: Degree in a technical field such as Applied Statistics, Mathematics and/or Computer Science, Software Engineering, etc. or equivalent. Preference will be given to candidates with relevant Microsoft Certifications and other field-related certifications. Experience leveraging big data technologies (one or more of Hadoop, Python, Spark) is required. Experience developing Extract-Transform-Load processes and tools (e.g. Informatica, SSIS, Azure Data Factory) (One or more, Azure Data Factory preferably). Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Experience working with and analyzing structured, semi-structured, and unstructured datasets. Knowledge of data modelling approaches and best practices. Solid understanding of relational and dimensional database design and knowledge of logical and physical data models. Familiarity with the Microsoft Azure platform, knowledge of core data services such as: Azure Data Factory Azure Storage Azure Synapse, SQL Server, Azure Analysis Services Azure Data Lake Gen 2 Experience with Source Code Version Control Systems such GitHub, TFS, Bitbucket. Familiarity with scripting languages like PowerShell, Bash (one or more). Strong Experience with Microsoft Power BI and Data modeling (star / snowflake schemas, fact, and dimensional tables). Strong knowledge in DAX and M languages building efficient measures. Debugging and Performance tuning. Experience with Azure Databricks, Delta tables, and Python. Understanding of agile project approaches and methodologies. The following experiences and/or qualifications would be an asset: Experience with Azure DevOps CI/CD - Release, Deployment pipelines. Experience with Open APIs 2.0 / 3.0, Swagger. Familiarity with at least one programming languages such as C#, Java, JavaScript, Nodejs. Understanding of Object Oriented and Functional programming paradigms.