Senior Data Engineer

We are seeking a passionate and skilled Senior Data Engineer to join our dynamic team in King of Prussia, PA. In this role, you will lead the design and implementation of advanced data pipelines for Business Intelligence (BI) and reporting. Your expertise will transform complex data into actionable insights, driving significant business value for our clients. Key Responsibilities: Design and implement scalable and efficient data pipelines for BI and reporting. Define and manage key business Data Products, build automated dashboards, and develop analytic self-service capabilities. Write comprehensive technical documentation to outline data solutions and architectures. Lead requirements gathering, solution design, and implementation for data projects. Develop and maintain ETL frameworks for large real-world data (RWD) assets. Mentor and guide technical teams, fostering a culture of innovation. Facilitate the deployment and integration of AI models, ensuring data quality and compatibility with existing analytics infrastructure. Collaborate with cross-functional stakeholders to understand data needs and deliver impactful analytics and reports. Required Qualifications: Bachelor's or Master's degree in Computer Science, Information Systems, or a related field. 3+ years building and operating production data pipelines, including 2+ in a client-facing or consulting setting 4+ years of SQL experience. Proficiency in at least one modern scripting or programming language (e.g., Python, Java, Scala, NodeJS). Working knowledge of at least one of the following modern data warehousing solutions (Snowflake, Databricks, Microsoft Fabric) Experience working directly with business stakeholders to align data solutions with business needs. Preferred Qualifications: Familiarity with container technologies like Docker and Kubernetes. Proficiency with data visualization tools (e.g., Tableau, Power BI, Quicksight). Certifications in Snowflake, Azure Data Engineering, or Databricks Experience with Agile methodologies and project management tools (e.g., Jira). Familiarity with DevOps practices, particularly CI/CD for data solutions. Knowledge of emerging data architectures, including Data Mesh, Data Fabric, Multimodal Data Management, and AI/ML integration. Experience in technical pre-sales, solution demos, and proposal development. Experience with workflow orchestration tools like Apache Airflow. Knowledge of data transformation tools and frameworks such as dbt (Data Build Tool), PySpark, or Snowpark. Experience with open-source table formats (e.g., Apache Iceberg, Delta, Hudi). #J-18808-Ljbffr