Cloud Data Architect

<Job Summary>Ignite innovation and drive strategic data solutions as a Cloud Data Architect! In this dynamic role, you will lead the design, development, and implementation of scalable, secure, and efficient cloud-based data architJob Description:The Cloud Architect will be a key contributor to designing, evolving, and optimizing our company's cloud-based data architecture. This role requires a strong background in data engineering, hands-on experience building cloud data solutions, and a talent for communicating complex designs through clear diagrams and documentation. Must work EST hours.Strategy, Planning, and Roadmap Development: Align AI and ML system design with broader business objectives, shaping technology roadmaps and architectural standards for end-to-end cloud-driven analytics and AI adoption.Designing End-to-End AI/ML Workflows: Architect and oversee all stages of AI/ML pipeline development—data ingestion, preprocessing, model training, validation, deployment, monitoring, and lifecycle management within cloud environments.Selecting Technologies and Services: Evaluate and choose optimal cloud services, AI/ML platforms, infrastructure components (compute, storage, orchestration), frameworks, and tools that fit operational, financial, and security requirements.Infrastructure Scalability and Optimization: Design and scale distributed cloud solutions capable of supporting real-time and batch processing workloads for AI/ML, leveraging technologies like Kubernetes, managed ML platforms, and hybrid/multi-cloud strategies for optimal performance.MLOps, Automation, and CI/CD Integration: Implement automated build, test, and deployment pipelines for machine learning models, facilitating continuous delivery, rapid prototyping, and agile transformation for data and AI-driven products.Security, Compliance, and Governance: Establish robust protocols for data access, privacy, encryption, and regulatory compliance (e.g., GDPR, ethical AI), coordinating with security experts to continuously assess risks and enforce governance.Business and Technical Collaboration: Serve as the liaison between business stakeholders, development teams, and data scientists, translating company needs into technical solutions, and driving alignment and innovation across departments.Performance Evaluation & System Monitoring: Monitor infrastructure and AI workloads, optimize resource allocation, troubleshoot bottlenecks, and fine-tune models and platforms for reliability and cost-efficiency at scale.Documentation and Best Practices: Create and maintain architectural diagrams, policy documentation, and knowledge bases for AI/ML and cloud infrastructure, fostering a culture of transparency, learning, and continuous improvement.Continuous Innovation: Stay abreast of new technologies, frameworks, trends in AI, ML, and cloud computing, evaluate emerging approaches, and lead strategic pilots or proofs-of-concept for next-generation solutions.This role blends leadership in technology and systems architecture with hands-on expertise in cloud infrastructure, artificial intelligence, and machine learning, pivotal for driving innovation, scalability, and resilience in a modern enterprise. Required Qualifications· Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field.· Minimum of 5 years of hands-on data engineering experience using distributed computing approaches (Spark, Map Reduce, DataBricks)· Proven track record of successfully designing and implementing cloud-based data solutions in Azure· Deep understanding of data modeling concepts and techniques.· Strong proficiency with database systems (relational and non-relational).· Exceptional diagramming skills with tools like Visio, Lucidchart, or other data visualization software. Preferred Qualifications· Advanced knowledge of cloud-specific data services (e.g., DataBricks, Azure Data Lake).· Expertise in big data technologies (e.g., Hadoop, Spark).· Strong understanding of data security and governance principles.· Experience in scripting languages (Python, SQL). Additional Skills· Communication: Exemplary written and verbal communication skills to collaborate effectively with all teams and stakeholders.· Problem-solving: Outstanding analytical and problem-solving skills for complex data challenges.· Teamwork & Leadership: Ability to work effectively in cross-functional teams and demonstrate potential for technical leadership.ectures. You will harness your expertise in big data technologies, data modeling, and cloud platforms to enable organizations to unlock the full potential of their data assets. Your proactive approach will shape how data is collected, stored, and analyzed across diverse business functions, empowering teams with actionable insights and fostering a data-driven culture. <Responsibilities> Design and architect robust cloud data solutions that support enterprise-wide analytics, reporting, and machine learning initiatives. Develop comprehensive data models and schemas to optimize storage efficiency and query performance within cloud environments such as AWS, Azure Data Lake, or similar platforms. Lead the integration of diverse data sources using ETL (Extract, Transform, Load) processes with tools like Informatica, Spark, or custom scripts in Java or Python. Implement NoSQL databases (e.g., DynamoDB, Cassandra) alongside traditional relational databases like Microsoft SQL Server and Oracle to accommodate varied data types and access patterns. Collaborate with cross-functional teams in Agile settings to translate business requirements into scalable technical solutions. Ensure data security, compliance, and governance standards are maintained throughout all architecture designs. Optimize big data processing workflows leveraging Hadoop, Spark, and other distributed computing frameworks for high-performance analytics. Support the development of data warehouses and lakes such as Azure Data Lake or similar platforms to facilitate advanced analytics and reporting. Maintain documentation of architecture designs, best practices, and technical standards for ongoing reference and team knowledge sharing. <Skills> Deep expertise in cloud platforms including AWS and Azure Data Lake services. Strong knowledge of NoSQL databases such as DynamoDB or Cassandra alongside traditional RDBMS like SQL Server and Oracle. Proven experience with big data technologies including Hadoop, Spark, and related ecosystems. Proficiency in programming languages such as Java, Python, Bash (Unix shell scripting), enabling automation and custom integrations. Solid understanding of data modeling principles for both relational and non-relational databases. Hands-on experience with ETL tools like Informatica or equivalent frameworks for seamless data ingestion. Familiarity with SQL query optimization for large datasets across multiple database systems. Knowledge of Linked Data concepts to facilitate semantic interoperability across datasets. Agile methodology experience to promote iterative development cycles aligned with business priorities. Strong analytical skills to interpret complex datasets and translate findings into actionable insights for stakeholders. Embark on a journey where your expertise transforms raw data into strategic assets! Join us to shape innovative cloud architectures that empower organizations to thrive in a digital-first world! Job Type: Contract Work Location: In person