Job

The Data Ops engineer will play a critical role in leading the design and execution phases of our Database Infrastructure project.
This person will work closely with cross-functional teams and stakeholders to ensure the successful delivery of a new data infrastructure.
Join us and make a substantial difference in a dynamic, forward-thinking environment.
 

We are looking for a Data Ops Engineer...

• What do we mean by “Data Ops”: this is a person with DBA skills and is very strong on cloud native (Azure ideally) tooling around Data storage, access, scaling, and optimization.

• Demonstrable experience horizontally scaling database architectures in a cloud environment.

• A work history of solving hard optimization problems to improve distributed data processing environments' efficiency (increased performance and lowered cost).

• Several years experience as an Application Software Engineer, Full Stack Developer, or similar role, developing and maintaining complex software applications.

• Resourcefulness, self-organization and self-management, and a strong problem-solving mindset.

• Strong leadership skills with the ability to contribute to and mentor other engineers.

• Flexibility to work with a team operating in different time zones.

• Excellent communication skills, with the ability to present projects and features to
  a diverse stakeholder audience.

• Experience working in an Agile environment, with knowledge of scrum
  ceremonies, procedures, and tools (such as Atlassian Confluence and JIRA).

• Demonstrated success as both a backend and frontend engineer.
   

Requirements

• At least 10 years of experience managing mission critical production workloads on relational (SQLServer, MySQL and PostgreSQL) and non relational databases (MongoDB, Cassandra) plus other Cloud native databases in a large, complex environment.

• Database administration, including configuration, implementation, data modeling, maintenance, redundancy/HA/DR, security, governance, troubleshooting/performance tuning, upgrades, database, data and server migrations (Flyway and Liquibase).

• Stored procedures

• Search and analytics engine: Elastic 

• Data integration: Kafka and Debezium.

• Data storage: Hadoop, AWS S3 or Azure Blob Storage

• Data warehouse: Redshift or Snowflake

• Orchestration: Apache Airflow

• Azure Data Factory

• Azure Stream Analytics & Event Hubs

• At least 5 years experience using Python in complex data engineering tasks.

• Python frameworks: PySpark

• Python libraries such as Panda and SQLAlchemy

• SQL migrations within a cloud (SQL databases to SQL managed instances and
  between clouds providers (Azure to AWS)

• Infrastructure as code (IaC) principles and experience with tools such as
  Terraform (preferably) or Ansible

 

Nice to have 

• Containerization and orchestration (Docker, Kubernetes)

• Data flow automation system: Apache NiF

• ELK stack.

• Azure functions

• Git and GitHub

• CI/CD implementations for data systems, including Blue-Green deployments

• Atlassian Tools: Jira, Confluence

???????Compensation

• $70 - $90 / Hr