Cloud Engineer Senior

Cloud Developer

Location: Must be onsite in McLean, VA starting April 2022

Work Authorization: This requirement is open to sponsored candidates through sub-vendors - one layer deep. The candidates must be W2 employees of the sub vendor and have at least three years remaining on their current visa.

Extension/Conversion: This is a 12 month contract position

Technical Must Haves: Python, Pyspark, AWS Services (SPECIFICALLY AWS Snowflake), Cubeflow, Kubernetes.

All candidates must be either a US Citizen or hold a Permanent Resident Card as well as be a direct W-2 employee to our vendors. A successful candidate will have the following characteristics:

• Knowledge & experience in building OAuth solutions. Knowledge of authentication, authorization of services via OAuth.
• Experience in understanding and implementing against technical IAM architecture designs across six major capability areas:
• Identity Lifecycle Management
• Identity Data Models
• Access Lifecycle Management
• Runtime Enforcement
• Credential Management
• Identity Federation
• Cleanse, manipulate and analyze large datasets (Structured and Unstructured data - XMLs, JSONs, PDFs) using Cloud platform (AWS with Kubernetes or GCP with Kubernetes).
• Develop Python, PySpark, Spark scripts to filter/cleanse/map/aggregate data.
• Improve the Query performance, understand and implement required Containerization
• Experience with large consumer data sets used in performance marketing is a major advantage
• Well-versed in (or contributes to) data-centric open-source projects
• Experience in performance analysis and optimization of data engineering pipelines for applications, e.g., in optimizing code written by others
• Programming Languages experience in Python, PySpark and Spark (Execution, Configuration, Containerization, etc.) for data ingestion.
• Presence or contributions to projects within the wider open-source ecosystem
• Proven ability to communicate both verbally and in writing within a high performance, collaborative environment.
• Exposure to commonly used relational and non-relational databases e.g., RedShift, Snowflake
• History of contributing to deployments in an engineering role.
• Knowledge of IT, service-oriented architectures, software development life cycles, or information security platforms and applications.

Requirements:

• Bachelors degree in Computer Science, Statistics, Data science or a related quantitative field.
• 4+ years of experience in processing large volumes and variety of data (Structured and unstructured data, writing code for parallel processing, XMLS, JSONs, PDFs)
• 3+ years of experience authoring, supporting, or providing a data science platform to data scientists
• Deep knowledge in the machine learning lifecycle, and in ways to facilitate collaboration and productivity in each of its phases.
• Exposure to a number of data scientists and expertise in finding solutions to workflow problems.
• Knowledge of common machine learning frameworks and libraries and in ways to productionalize their inputs and outputs
• Comfort with various machine learning techniques and their practical implementation, particularly reinforcement learning
• Experience with one or more common workflow / pipelining frameworks (Kubeflow, MLFlow, Argo or equivalents)
• Strong knowledge of the Python ecosystem, the Jupyter ecosystem (Lab and Notebook) and their libraries, norms and tooling
• Experience in cloud storage configuration (S3, MinIO, etc.)
• Exposure to AutoML tooling (DataRobot or equivalents)
• Experience in deploying and maintaining enterprise-scale machine learning applications in production
• Experience with developing and deployment of front-end User interface for web application using ReactJS or Express or HTML5.
• Experience with developing and deployment web applications using Flask or Python based open- source framework
• Experience with development and deployment of web applications with Python based data objects for databases e.g., DB2, Oracle, SnowFlake
• 2+ years of experience writing well-tested production software
• 1+ years of experience on distributed, high throughput and low latency architecture.
• 1+ years of experience building software on top of major container technology (Kubernetes, docker, or similar).
• Strong testing mindset with experience writing tests at various levels of granularity
• Familiarity with Continuous Integration tools (GitHub actions, Travis-CI, etc.)
• A history of good collaboration with DevOps and Project Managers on meeting project goals.
• Proven track record working with products from major cloud providers (AWS, GCP, Azure, etc.