Cloud Engineer

AWS Cloud Data Engineer – Contract Akkodis is seeking an AWS Cloud Data Engineer for a contract role onsite in Cambridge, VT. The ideal candidate is a senior‑level technical engineer with experience building pipelines, training and deploying models, governing data with Unity Catalog/Lake Formation, and improving performance and reliability at scale. Rate and Location $48–$53 per hour, negotiable based on experience, education, geographic location and other factors. Onsite in Cambridge, VT. Key Skills AWS Cloud Data Lake – Expert with SageMaker, S3, EMR, Glue, Lambda, Redshift, Athena, Step Functions, Lake Formation, and IAM security best practices. Design & management of AWS Data Lake architectures. Databricks – Expert in large‑scale data engineering, ML model development, MLflow, and Unity Catalog. Big Data Processing – Advanced with Apache Spark (PySpark/Scala), distributed computing, and processing large‐scale structured/unstructured data. Machine Learning – Solid expertise in ML algorithms, feature engineering, model evaluation, and frameworks such as scikit‑learn, XG-Boost, TensorFlow, or PyTorch. MLOps – Proven experience with end‑to‑end ML lifecycle, deployment, monitoring, retraining, CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes/ECS). Python – Expert‑level proficiency for data science and ML workflows. SQL – Advanced SQL for data analysis and pipeline development. Code Management – Proficiency with Git, branching strategies, and code review practices. Key Responsibilities Lead strategy, managing a team of 6 data scientists, ML engineers and analytics professionals across onshore/offshore locations. Define and drive the data science operations strategy, roadmap and best practices aligned with business objectives. Partner with senior business stakeholders and product owners to identify high‑impact AI/ML opportunities and translate them into actionable project plans. Govern standards for model development, deployment, monitoring and responsible AI adoption. Hands‑on technical delivery: architect scalable ML pipelines for data ingestion, feature engineering, model training, validation and inference on AWS and Databricks. Design and implement AWS Data Lake architectures and big‑data processing solutions for petabyte‑scale structured and unstructured data. Lead deployment of production ML systems, including real‑time inference APIs, batch prediction pipelines and model‑as‑a‑service architectures. Drive MLOps maturity: CI/CD for ML, automated model retraining, drift detection, A/B testing and performance monitoring. Benefits Benefits include medical, dental, vision, life insurance, short‑term disability, voluntary benefits, an EAP program, commuter benefits and a 401(k) plan. Associates may be eligible for paid leave (Paid Sick Leave, holiday pay, etc.) as required by law. Equal Opportunity Employer Equal Opportunity Employer. Veterans/Disabled. Military‑connected talent encouraged to apply. Requirements / Equal Employment Opportunity The Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements. California Fair Chance Act Los Angeles City Fair Chance Ordinance Los Angeles County Fair Chance Ordinance for Employers San Francisco Fair Chance Ordinance Massachusetts: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. #J-18808-Ljbffr Akkodis