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Job Location: Phoenix, AZ
Job Detail:
Job Description:
Agile Project Work: Work in cross-functional, geographically distributed agile teams of highly skilled data engineers, software/machine learning engineers, data scientists, DevOps engineers, designers, product managers, technical delivery teams, and others to continuously innovate analytic solutions.
Design, develop, and review real-time/bulk data pipelines from a variety of sources (streaming data, APIs, data warehouse, messages, images, video, etc).
Follow established design patterns for data ingest, transformation, and egress.
Develop documentation of Data Lineage and Data Dictionaries to create a broad awareness of the enterprise data model and its applications.
Apply best practices within DataOps (Version Control, P.R. Based Development, Schema Change Control, CI/CD, Deployment Automation, Test Automation, Shift left on Security, Loosely Coupled Architectures, Monitoring, Proactive Notifications)
Problem-Solving/Project Management: Constructively challenge while soliciting participation in problem-solving to enrich possible solutions.
Architecture: Utilize modern cloud technologies and employ best practices from DevOps/DataOps to produce enterprise-quality production Python and SQL code with minimal errors.
Participate in regular code review sessions and collaboratively discuss opportunities for continuous improvement in all solutions.
Self-Development: Flexibly seek out new work or training opportunities to broaden experience.
Independently research the latest technologies and openly discuss applications within the department.
Perform other duties as requested.
Qualifications:
Minimum Requirements:
Bachelors degree in engineering, computer science, analytical field (Statistics, Mathematics, etc.), or related discipline and three (3) years of relevant work experience.
Masters or Ph.D. in engineering, computer science, analytical field (Statistics, Mathematics, etc.), or related discipline and one (1) year of relevant work experience.
Strong experience in at least two areas:
Knowledgeable Practitioner of SQL development with experience designing high-quality, production SQL codebases.
Knowledgeable Practitioner of Python development with experience designing high-quality, production Python codebases.
Knowledgeable Practitioner in data engineering, software engineering, and Client systems architecture.
Knowledgeable Practitioner of data modeling.
Experience applying software development best practices in data engineering projects, including Version Control, P.R. Based Development, Schema Change Control, CI/CD, Deployment Automation, Test Driven Development/Test Automation, Shift left on Security, Loosely Coupled Architectures, Monitoring, Proactive Notifications using Python and SQL.
Data science experience wrangling data, model selection, model training, modeling validation, e.g., Operational Readiness Evaluator and Model Development and Assessment Framework, and deployment at scale.
Preferred Qualifications:
Working knowledge of Azure Stream Architectures, DBT, Schema Change tools, Data Dictionary tools, Azure Machine Learning Environment, GIS Data.
Working knowledge of Software Engineering and Object Orient Programming Principles.
Working knowledge of Distributed Parallel Processing Environments such as Spark or Snowflake.
Working knowledge of problem-solving/root cause analysis on Production workloads.
Working knowledge of Agile, Scrum, and Kanban.
Working knowledge of workflow orchestration using tools such as Airflow, Prefect, Dagster, or similar tooling.
Working knowledge with CI/CD and automation tools like Jenkins or Azure DevOps.
Experience with containerization tools such as Docker.
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