Cloud Data Architect

• Provide technical direction, implement technical standards
• Provide evaluations and prototypes for novel ideas and technologies
• Create skills to be transferred to operational development teams
• Analyze difficult issues and participate actively in business technology design decisions
• Accept responsibility for modernizing and moving to a cloud data platform
• Design and construct a dependable, scalable data infrastructure that uses cutting-edge privacy and security measures to protect data
• Create solutions for predictive and prescriptive analytics that are scalable, secure, low-latency, resilient, and affordable for the entire organization
• Create/Architect frameworks that provide serverless architecture and unsupervised continuous training for machine learning models
• Data models like Tableau, DynamoDB, and Kibana should be managed and scaled
• Share work progress with internal and external stakeholders
• Using best practices in data modeling, ETL/ELT procedures, and data engineer handoff, develop frameworks for real-time and batch data import pipelines
• Work with knowledgeable coworkers and take part in technical decisions
• Review the implementations and code, and offer insightful criticism to assist others in creating better solutions

Job Requirements:

• Bachelor s/Master s degree in Engineering, Computer Science (or equivalent experience)
• At least 7+ years of relevant experience as a Cloud Data Architect
• 7+ years of experience working directly with enterprise data solutions
• 7+ years of implementation experience on IT platforms
• Prolific knowledge of public cloud environment and on-prem infrastructure
• Extensive experience with Columnar Databases like Redshift Spectrum, Time Series data stores like Apache Pinot, and the AWS cloud infrastructure
• Demonstrable experience with in-memory, serverless, streaming technologies and orchestration tools like Spark, Kafka, Airflow, and Kubernetes
• In-depth knowledge of AWS Certified Big Data is desirable
• Nice to have some experience with AWS big data and analytics solutions in large digital and retail environments
• Extensive experience with databases, data lakes, and schemas for online transactional (OLTP) and analytical processing (OLAP)
• Working knowledge of the Kinesis/Kafka, S3, Glue, and Athena operational technologies in the AWS Cloud Data Lake
• Knowledge of any of the following message/file formats - Plywood, Avro, and ORC
• Proficient knowledge of EMS, MQ, Java, XSD, File Adapter, and ESB-based systems, as well as other streaming services
• Extensive knowledge of distributed designs, including data integration architectures and microservices, SOA, and RESTful APIs
• Broad range of experience with contemporary data processing technologies, such as the Big Data Stack (Spark, Spectra, Flume, Kafka, Kinesis, etc.).
• Knowledge of data streaming technologies, such as Kafka and SQS/SNS queuing, to the highest degree
• Solid understanding of Redshift, Snowflake, and Firebolt columnar databases
• Knowledge of Python, PySpark, or other related programming languages
• Familiarity with BI technologies like Tableau, Domo, and MicroStrategy
• Great comprehension of continuous integration and delivery
• Strong knowledge of S3, Lambda, Redshift, Glue, and EC2 among other frequently used AWS services
• Excellent spoken and written English communication skills