Data Engineer Manager Jobs in Vermont (NOW HIRING)

Job Summary:
Diverse Lynx is seeking an AWS Cloud Data Lake Lead to manage a team of data scientists and ML engineers. The role involves defining data science operations strategy, architecting scalable ML pipelines, and overseeing AWS Data Lake architectures.
Responsibilities:
• Lead and manage a team of 6 data scientists, ML engineers, and analytics professionals across onshore/offshore locations, providing technical mentorship and career guidance.
• Define and drive the data science operations strategy, roadmap, and best practices aligned with business objectives.
• Partner with senior business stakeholders, product owners, and cross-functional teams to identify high-impact AI/ML opportunities and translate them into actionable project plans.
• Establish and govern standards for model development, deployment, monitoring, and responsible AI adoption across the organization.
• Architect and oversee scalable ML pipelines for data ingestion, feature engineering, model training, validation, and inference on AWS cloud and Databricks.
• Design and implement AWS Data Lake architectures and big data processing solutions for structured and unstructured data at petabyte scale using Spark, Databricks, and AWS-native services (S3, Lake Formation, EMR, Glue, SageMaker, Redshift, Athena).
• Lead the deployment of production ML systems including real-time inference APIs, batch prediction pipelines, and model-as-a-service architectures.
• Drive MLOps maturity CICD for ML, automated model retraining, drift detection, AB testing, and performance monitoring.
Qualifications:
Required:
• Deep hands-on experience with AWS services SageMaker, S3, EMR, Glue, Lambda, Redshift, Athena, Step Functions, Lake Formation, and IAM security best practices.
• Proven experience designing and managing AWS Data Lake architectures.
• Proficiency in Databricks for large-scale data engineering, ML model development, MLflow for experiment tracking, and Unity Catalog for governance.
• Strong experience with Apache Spark (PySpark/Scala), distributed computing, and processing large-scale structured/unstructured datasets.
• Solid expertise in ML algorithms, feature engineering, model evaluation, and frameworks such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Proven experience with end-to-end ML lifecycle model deployment, monitoring, retraining, CICD pipelines, containerization (Docker), and orchestration (Kubernetes/ECS).
• Expert-level proficiency in Python for end-to-end data science and ML workflows.
• Advanced SQL for data analysis and pipeline development.
• Proficiency with Git, branching strategies, and code review practices.
• Lead and manage a team of 6 data scientists, ML engineers, and analytics professionals across onshore/offshore locations, providing technical mentorship and career guidance.
• Define and drive the data science operations strategy, roadmap, and best practices aligned with business objectives.
• Partner with senior business stakeholders, product owners, and cross-functional teams to identify high-impact AI/ML opportunities and translate them into actionable project plans.
• Establish and govern standards for model development, deployment, monitoring, and responsible AI adoption across the organization.
• Architect and oversee scalable ML pipelines for data ingestion, feature engineering, model training, validation, and inference on AWS cloud and Databricks.
• Design and implement AWS Data Lake architectures and big data processing solutions for structured and unstructured data at petabyte scale using Spark, Databricks, and AWS-native services (S3, Lake Formation, EMR, Glue, SageMaker, Redshift, Athena).
• Lead the deployment of production ML systems including real-time inference APIs, batch prediction pipelines, and model-as-a-service architectures.
• Drive MLOps maturity CICD for ML, automated model retraining, drift detection, AB testing, and performance monitoring.
Company:
Diverselynx IT Consulting Services Founded in 2002, the company is headquartered in Princeton, USA, with a team of 1001-5000 employees. The company is currently Late Stage.