Certifications Minimum: Google Professional Data Engineer Preferred: AWS Machine Learning Specialty Certification
7+ years in a customer facing role working with enterprise clients
4+ years of experience working in enterprise data warehouse and analytics technologies Hands-on experience building and training machine learning models.
Experience writing software in one or more languages such as Python, Scala, R, or similar with strong competencies in data structures, algorithms, and software design.
Experience working with recommendation engines, data pipelines, or distributed machine learning.
Experience working with deep learning frameworks (such as TensorFlow, Keras, Torch, Caffe, Theano).
Strong coding skills in Python and familiarity with ML/DL libraries like TensorFlow, PyTorch, or JAX.
Knowledge of data analytics concepts, including data warehouse technical architectures, ETL and reporting/analytic tools and environments (such as Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).
Customer facing experience of discovery, assessment, execution, and operations. Demonstrated excellent communication, presentation, and problem solving skills.
Experience in project governance and enterprise customer management.
Proficiency in building Graph Neural Networks (GNNs) using frameworks like DGL, PyTorch Geometric, or similar.
Experience with ScaNN or other approximate nearest neighbor (ANN) techniques for vector similarity search.
Hands-on experience with Google Cloud Platform (GCP) tools such as Vertex AI, BigQuery, and Dataflow.
Strong problem-solving and communication skills, including the ability to work with clients and cross-functional teams.