DataOps EngineerRequirements:Bachelor's degree in Computer Science, Computer Engineering, or a related technical degree; four years related experience; or equivalent combination of education and experience2+ years experience in data streaming technologies, such as Kafka2+ years experience using ETL (Extract, Transform, and Load) conceptsExperience with querying and designing databases using one or more of the following: MySQL, MS SQL, Oracle SQL, or other professional database systemAbility to work in teams and collaborate with others to clarify requirements, quickly identify problems, and collaboratively find creative solutionsAbility to assist in documenting requirements as well as resolve conflicts or ambiguitiesNice to Have Skills:4 or more years experience in programming using one or more of the following: Java, C++, Perl, Python, or advanced Shell scripting.3 or more years of experience in implementing data-driven solutions using tools such as Hadoop, Impala, Hive, NiFi, Athena, Redshift, BigTable, or Airflow.2 or more years experience in machine learning and statistical modelingExperience in Cloud Native tools, such as Kubernetes and DockerExperience with using the R statistical computing languageExperience with Agile at Scale, SAFe, and Lean Systems EngineeringResponsibilities:Develop high-volume, low-latency, data-driven solutions utilizing current and next generation technologies to meet evolving business needsAcquire big data input from numerous partners. Key technologies may include Python, Airflow, Prometheus, and Kafka.Normalize complicated data sources to convert potentially unusable data into a format that can be efficiently used by software and/or employees. Key technologies may include Spark, Kinesis, LambdaBuild a CI/CD pipeline for our data software to ensure we keep quality high and time to market low.
Key technologies may include Gitlab.