Sr. Data / M/L Engineer

Location Hybrid on site in Union Square, NY. Objectives Design and implement advanced analytical solutions Build and optimize data pipelines and ETL frameworks Develop machine learning models for predictive and prescriptive analytics Establish scalable data infrastructure Enable business teams through insights, dashboards, and reporting capabilities Responsibilities The applicant will design, develop, and implement analytical solutions to support business decisions. This includes applying statistical and machine learning techniques to large datasets for predictive and prescriptive analysis, building data pipelines and ETL processes, and collaborating with cross‑functional teams to define data requirements. The role also involves creating dashboards and reports using BI tools such as Power BI and Tableau, writing complex SQL queries, managing data in relational and SQL databases, and documenting data processes, models, and tools. Full‑stack knowledge is required to set up new infrastructure, manage hardware and servers, run compilers and interpreters, and implement machine learning and AI techniques. Experience with AWS and other cloud platforms is essential for scalable storage and processing. Key Skills Strong SQL and database management experience Experience with data pipelines and ETL processes Proficiency in machine learning and statistical modeling Experience with BI tools (Power BI, Tableau) Full‑stack development knowledge Experience with cloud platforms (AWS preferred) Strong understanding of data architecture, data modeling, and infrastructure setup Ability to work with large‑scale datasets and programming experience in Python or R Strong problem‑solving and analytical skills Preferred Skills Experience with AI and advanced machine learning frameworks Familiarity with big data technologies (Spark, Hadoop, etc.) Experience setting up new environments and infrastructure from scratch Knowledge of hardware/server configuration Experience in energy/utilities or highly regulated industries DevOps or data engineering tooling experience Education Bachelor’s degree in Electrical Engineering or Computer Engineering. #J-18808-Ljbffr Aquent