Cloud Data Architect

Industry: Retail
Remote
Company size: 10K+
Full-time/Part-time
Not disclosed

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Job description

A US-based company that offers customers the fastest, easiest way to find all kinds of musical gear they need in one place is looking for a Cloud Data Architect. The selected candidate will provide a strong leadership role in developing the enterprise data architecture of digital and retail businesses across the company. The company has more than 255 stores across the nation, and their team of experienced musicians will help customers to find the right piece of gear for their band, ensemble or music venue. The company has managed to raise more than $30mn in funding so far. This role requires some overlap with the PST time zone. 

 

Job Responsibilities:

  • Provide technical guidance architecture, and enforce technical standards
  • Provide assessments and prototyping of new concepts and technologies
  • Develop capabilities to be handed off to operational development teams
  • Provide analysis on complex problems as well as be an active member of enterprise technology design decisions
  • Accountable for modernization, migration/transformation to a cloud data platform
  • Design and build reliable, scalable data infrastructure with leading privacy and security techniques to safeguard data
  • Architect scalable, secure, low-latency, resilient, and cost-effective predictive and prescriptive analytics systems for the entire enterprise
  • Design/Architect frameworks to allow unsupervised continuous training models and operationalize ML models using serverless architecture
  • Take over and scale our data models (Tableau, DynamoDB, Kibana)
  • Communicate with both internal and external stakeholders on work progress
  • Create frameworks for real-time and batch data import pipelines, utilizing best practices in data modeling, ETL/ELT processes, and data engineer handoff.
  • Participate in technical decisions and work with skilled colleagues.
  • Review the code and implementations, as well as provide useful feedback to help others build better solutions
  • Boost the technology direction and make suggestions based on experience and research

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 7+ years of relevant experience as a software engineer
  • 7+ years of experience working directly with enterprise data solutions
  • Competency working in a public cloud environment and on-prem infrastructure
  • Expertise in Columnar Databases like Redshift Spectrum, Time Series data stores like Apache Pinot, and the AWS cloud infrastructure
  • Experience with in-memory, serverless, streaming technologies and orchestration tools like Spark, Kafka, Airflow, and Kubernetes
  • 7+ years of hands-on implementation experience in IT platforms is requires
  • Nice to have some knowledge of AWS Certified Big Data
  • Demonstrable ability working with AWS big data and analytics solutions in large digital and retail environments is desirable
  • Advanced knowledge and experience in online transactional (OLTP) processing and analytical processing (OLAP) databases, data lakes, and schemas
  • Sound knowledge of AWS Cloud Data Lake Technologies and operational expertise of Kinesis/Kafka, S3, Glue, and Athena
  • Familiarity with any of the message/file formats: Parquet, Avro, ORC
  • Prolific skills in working with streaming services like EMS, MQ, Java, XSD, File Adapter, and ESB based applications
  • Extensive experience in distributed architectures like Microservices, SOA, RESTful APIs, and data integration architectures
  • Experience with a wide variety of modern data processing technologies like Big Data Stack (Spark, spectrum, Flume, Kafka, Kinesis, etc.)
  • Prolific knowledge of Data streaming technologies like Kafka and SQS/SNS queuing
  • Knowledge of Columnar databases like Redshift, Snowflake, and Firebolt
  • Experience with commonly used AWS services like S3, Lambda, Redshift, Glue, and EC2
  • Core understanding of Python, pySpark, or similar programming languages
  • Knowledge of BI tools like Tableau, Domo, and MicroStrategy
  • Understanding of Continuous Integration / Continuous Delivery

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