Job Description

DataOps Engineer Requirements:

Bachelor's degree in Computer Science, Computer Engineering, or a related technical degree; four years related experience; or equivalent combination of education and experience
2+ years experience in data streaming technologies, such as Kafka
2+ years experience using ETL (Extract, Transform, and Load) concepts
Experience with querying and designing databases using one or more of the following: MySQL, MS SQL, Oracle SQL, or other professional database system
Ability to work in teams and collaborate with others to clarify requirements, quickly identify problems, and collaboratively find creative solutions
Ability to assist in documenting requirements as well as resolve conflicts or ambiguities

Nice 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 modeling
Experience in Cloud Native tools, such as Kubernetes and Docker
Experience with using the R statistical computing language
Experience with Agile at Scale, SAFe, and Lean Systems Engineering

DataOps Engineer Responsibilities:

Develop high-volume, low-latency, data-driven solutions utilizing current and next generation technologies to meet evolving business needs
Acquire 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, Lambda
Build a CI/CD pipeline for our data software to ensure we keep quality high and time to market low. Key technologies may include Gitlab.

Department: Preferred Vendors
This is a contract position

Job Tags

Contract work

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