Solutions Architect (Managed Services)

Production support of enterprise data platforms such as Snowflake, AWS, Azure, or Databricks. Extensive experience in providing architectural guidance and operational support across a large user base for a cloud-native data warehouse (Snowflake and/or Redshift) with a background in Systems Engineering, DevOps, DBA or Data Architect. Production experience working with Cloud and Distributed Data Storage technologies such as S3, ADLS, HDFS, ElasticSearch/Solr, Cassandra or other NoSQL storage systems. Production experience working with Data integration technologies such as Spark, Kafka, event/streaming, Fivetran, HVR, NiFi, AWS Data Migration Services, Azure DataFactory or others. Production experience working with Workflow Management and Orchestration such as Airflow, AWS Managed Airflow, Luigi, NiFi. Strong working knowledge of SQL and the ability to write, debug, and optimize SQL queries. Deep expertise with cloud-native data technologies in AWS or Azure. Professional track record of creating, challenging, and improving processes and procedures. Unmatched troubleshooting and performance tuning skills. Provide team lead and mentorship of engineers. Passion for learning new technology stacks and experience as a technical and up-skill/training team member. Create and deliver detailed technical presentations for an executive audience. Excellent client-facing written and verbal communication skills and experience. Extensive experience with infrastructure as code using Terraform or Cloud Formation (Preferred). Proven expertise using Python to build automated solutions for repetitive support tasks (Preferred). Well-versed with continuous integration and deployment frameworks with hands-on experience using CI/CD tools like Bitbucket, Github, Flyway, and Liquibase (Preferred). Snowflake SnowPro Core certification (Preferred).

Propose, design, and provision cloud-native data solutions on AWS/Azure. Leverage deep understanding of Snowflake, IAM, S3, EC2, Kinesis, Sagemaker, Airflow, Kafka, Azure Data Factory, ADLS, Fivetran, DBT, and/or other services and tools. Lead a technical team operating and managing modern data platforms. Provide clear ownership of multiple simultaneous customer accounts as the technical leader. Build Epics, Stories, and Tasks to mature and improve customer data platforms. Delegate to and coach Engineers. Provide thought leadership by recommending the right technologies and approaches. Lead discussions and contribute to design recommendations for data model design. Continually hunt for ways to automate, optimize, and expand customer data platforms.