Data Engineer

Data Engineer
Responsibilities

• Develop and maintain scripts and tools using Python, PowerShell, and R.
• Design, write, and optimize SQL queries for performance and scalability.
• Help modernize 'legacy' solutions to realign with our current code base and tech stack.
• Assist in redevelopment, improvement and ongoing maintenance of existing data, analytics, and reporting solutions.
• Ensure accurate and efficient data integration of diverse data sources and formats.
• Enhance and support database functions and procedures.
• Optimize data access and data processing workflows for performance, scalability, and efficiency/
• Implement data quality checks and validations to ensure the accuracy, consistency, and completeness of data.
• Identify and resolve performance bottlenecks, investigate and troubleshoot data related issues, and provide solutions to address defects.
• Seamlessly transition between production support and development tasks based on business needs.
• Deploy and manage code utilizing engineering best practices in non-prod and prod environments.

Requirements:

• Bachelor's Degree in computer science, data science, software engineering, information systems, or related quantitative field.
• Minimum 4 years of experience working as a Python Developer, Solutions Engineer, Data Engineer, or similar roles.
• 4+ years of solid continuous experience in Python.
• 3+ years of solid experience writing SQL and PL/SQL code.
• 3+ years of experience working with relational databases (solid understanding of Oracle preferred).
• 2+ years of experience scripting with PowerShell.
• Experience programming in R.
• Experience with web application frameworks including Shiny, Dash, Streamlit.
• Experience with CI/CD utilizing git/Azure DevOps.
• Knowledge of alternative storage formats including Parquet/Arrow/Avro.
• Ability to collaborate within and across teams of different technical knowledge to support delivery of solutions.
• Expert problem-solving skills, including debugging skills, enabling the determination of sources of issues in unfamiliar code or systems.

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