PricewaterhouseCoopers

Line of Service

Advisory

Industry/Sector

Technology

Specialism

Advisory - Other

Management Level

Senior Associate

Job Description & Summary

The Data Engineering Senior Associate helps evaluate requirements, assist in design discussions and sprint planning for the construction of data pipelines, Extraction, and Transformation logic. They will be competent in Python Programming, SOLID, and DRY Design principles. The SA Data Engineer will leverage their skills in relational databases, cloud storage, and data wrangling to support business decisions and insights. The role requires a strong foundation in data management practices and the ability to mentor junior engineers.

Key Responsibilities:

• Build, and maintain scalable data pipelines and architectures to process large volumes of data efficiently.
• Implement and manage relational databases and relational database management systems (RDBMS) using Python, SQL and other languages.
• Engage in data wrangling and cleaning processes to ensure data quality and consistency.
• Conduct code reviews and adhere to coding standards to maintain the quality and integrity of data engineering solutions.
• Collaborate with cross-functional teams to identify data requirements and implement appropriate data solutions.
• Mentor junior engineers and provide guidance on best practices in data engineering.

Required Skills & Experience:

• 5 years experience.
• SOLID and DRY Programming principles - The ability to plan, execute, and evaluate code for compliance with industry best practices
• Python Programing - The ability to write efficient, executable code for the creation of Data Pipelines
• Restful APIs - The ability to integrate API calls into dat streams
• Azure Databricks or similiar product (Microsoft Fabric, etc.) - Create Jupyter Notebooks using Python Libraries, create and manage workflows and pipeline
• Set Theory - foundational principles for handling data organization, relationships, and operations within large data sets. This knowledge allows them to efficiently manipulate, query, and integrate data, ensuring accurate and scalable solutions for complex data engineering tasks.

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date