Data Engineer

As a Data Engineer & Warehousing professional, your primary responsibilities will include managing the full development cycle of Data Engineering & Warehousing concepts, from requirements gathering to maintenance. You will be identifying and resolving data issues to ensure data quality and consistency, and implementing automation opportunities. Developing expertise in data and data models within the data warehouse, and understanding supported business domains will also be part of your role. Effective communication with technical personnel, business managers, and senior leadership regarding data inquiries and requests is essential. You will conduct internal testing & user acceptance testing, and develop technical specifications and design documents. Ensuring quality processes throughout the Development Lifecycle and implementing efficient functional design solutions is crucial. Collaborating with the Business and Business Intelligence team to meet requirements and build robust data pipelines is also a key responsibility. Designing and implementing scalable and secure data environments, new product features, and cutting-edge technologies is another aspect of your role. You will collaborate with the Data Science team on complex machine learning models to maximize model performance and apply domain technical expertise to provide solutions to the business and its operations. Qualifications required for this role: - Bachelor's Degree in computer science, Information Technology, Management Information Systems, or related field (Required); Technical MS Preferred - 5 years of professional experience in data engineering/data warehousing enterprise or related experience (Required) - Advanced skills in data warehouse architectures, dimensional models, star schema designs, and in-memory/columnar databases - Proficiency in programming languages such as Spark, Spark SQL, R, Python, Java, and Scala - Knowledge of Delta Lake and SQL & T-SQL skills - Proficient in SQL Server syntax, Microsoft/Azure services like Data Factory, & Azure Analysis Services (Tabular), and associated syntaxes (DAX, MDX) - Strong experience with Database Management Systems (DBMS), specifically SQL and NoSQL - Demonstrated success working within Azure Synapse Analytics and Azure Blob Storage - Working experience with API / RESTful data services and big data technologies such as Spark, Databricks, Hadoop, Hive, etc. - Knowledge of popular data discovery, analytics, and BI software tools like Power BI for semantic-layer-based data discovery - Familiarity with containerization techniques such as Docker, Kubernetes,