Cloud Data Architect

Industry: Retail

Remote

Company size: 10K+

Full-time/Part-time

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Job description

A U.S.-based company that caters to musicians and music enthusiasts by operating a chain of musical instrument stores, is looking for a Cloud Data Architect. The selected candidate will have a strong leadership role in developing the Enterprise data architecture of the company’s digital and retail businesses across different brands. The company has well over 500 retail locations across the U.S. that sell new and used musical instruments, and offer instrument rentals/repairs, as well as lessons to musicians of all ages and abilities. This business has successfully raised over $30 Million through debt financing. The job role requires a 7-8 hour overlap with IST and some overlap with the PST time zones.

Job Responsibilities:

Assess and create prototypes of new concepts and technologies
Develop essential capabilities that can be handed off to operational development teams
Analyze complex problems and actively participate in enterprise technology design decisions
Take ownership of modernizing, migrating, and transforming the cloud data platform
Safeguard data by designing and building reliable and scalable data infrastructure with leading privacy and security techniques
Architect solutions that are scalable, secure, low latency, resilient and cost-effective to enable predictive and prescriptive analytics across the organization
Design and develop frameworks that can effectively operationalize ML models through serverless architecture while supporting unsupervised continuous training models
Take ownership of scaling the company data models including Tableau, DynamoDB, and Kibana
Analyze data to share data-backed findings with technical and non-technical internal and external stakeholders
Use data modeling best practices to build frameworks for data ingestion pipelines - both real-time and batch, ETL/ELT processes, and effectively hand them off to data engineers
Collaborate with peers and actively participate in critical technical decisions
Review code, and code implementations to share constructive feedback
Utilize your experience and research to make recommendations that can drive technology direction and choices of technologies

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
Experience working directly with enterprise data solutions (7+ years)
Practical exposure to a public cloud environment and on-prem infrastructure
Highly skilled in Columnar Databases such as - Redshift Spectrum
Proficient with Time Series data stores like Apache Pinot
Significant understanding of AWS cloud infrastructure
Demonstrable experience with in-memory, serverless, streaming technologies and orchestration tools such as Kubernetes, Airflow, Spark, and Kafka
Hands-on experience implementing IT platforms (7+ years)
AWS Certification with Big Data would be highly desirable
Previous experience implementing and designing AWS analytics and big data solutions in a large digital and retail environment would be preferred
Thorough understanding of and experience in online transactional processing (OLTP) and online transactional analytical processing (OLAP) databases, data lakes, and schemas
Hands-on experience with AWS Cloud Data Lake Technologies and operational experience with Kinesis/Kafka, S3, Glue, and Athena
Familiarity with Parquet, Avro, or ORC message/file formats
Experience designing and developing Streaming Services, EMS, MQ, Java, XSD, File Adapters, and ESB-based applications
Strong understanding of distributed architectures such as Microservices, SOA, RESTful APIs, and data integration architectures
Experience with Big Data Stack- Spark, spectrum, Flume, Kafka, Kinesis, etc
Understanding of modern Data streaming technologies like Kafka, SQS/SNS queuing, etc
Familiarity with Columnar databases like Redshift, Snowflake, Firebolt, etc
Knowledge of commonly used AWS services such as- S3, Lambda, Redshift, Glue, and EC2
Expertise in Python, pySpark, or similar programming languages
Understanding of BI tools like Tableau, Domo, and MicroStrategy
Familiarity with CI/CD concepts
Excellent English communication skills

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