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