Sr. Data Engineer

Sr. Data Engineer (Cloud) Description As a Data Engineer, you'll be working with the latest cloud and technology stacks to help clients implement and mature their modern data architecture. You will work with tools/platforms like Kafka, Snowflake, and Databricks to help clients get the most out of their data that may be in systems like Salesforce, SAP, SQL Server, or file storage. With a variety of projects, technologies, and clients, you will constantly be growing, and never bored. Responsibilities At least 4 years of experience as a hands-on software or data engineer At least 1-2 years building production-grade data solutions (Example: ETL/ELT, Spark, Azure Data Factory, AWS Data Migration Services, streaming systems) Demonstrated aptitude for problem-solving and creativity Ability to learn new technologies and apply learnings to production-grade solutions Experience with at least one prominent cloud provider (e.g.: AWS, Azure, GCP) Strong working knowledge of a querying language like SQL Understanding of CI/CD, automated testing, and the DevOps culture Effectively communicate complex technical solutions to a variety of audiences through oral and written mediums Qualifications and Skills Production experience with at least one distributed data system like Snowflake, Databricks, Cassandra, DynamoDb, Elastic, or Hadoop Production experience with at least one messaging technology like Kafka, Kinesis, Pulsar, or RabbitMQ Certification on at least one relevant platform/tool (AWS, Azure, GCP, Snowflake, Databricks, Spark) Can translate business needs into optimized and efficient data models in SQL or NoSQL Service frameworks such as Spring Boot, Ratpack, Vert.x, or Play Knowledge of data analytics, visualization and governance Experience working in an agile development framework like Scrum or Kanban