Data Engineering Apprentice

Job Summary
The Data Engineering Apprentice will be part of the Digital Finance Data Engineering team and will support the design, development, and operation of enterprise data pipelines and data platforms. This role is intended for early career candidates who are eager to build strong foundations in modern data engineering practices while working in a governed, enterprise-scale environment.
The apprentice will work under the guidance of senior data engineers and managers, gaining hands-on experience with cloud data platforms, data integration, data modeling standards, and finance-domain datasets.

Key Responsibilities
Data Engineering & Platform Support
• Assist in building and maintaining data pipelines for ingesting, transforming, and validating data from various source systems.
• Support data transformations using SQL and Python under established engineering standards.
• Help with data quality checks, reconciliation processes, and basic troubleshooting of data issues.
• Participate in documenting data pipelines, table definitions, and engineering artifacts.
Learning & Engineering Practices
• Learn and apply modern data engineering practices including ELT/ETL pipelines, version control, and CI/CD fundamentals.
• Follow enterprise data engineering standards for naming conventions, data modeling, and code quality as defined by the team.
• Gain hands-on exposure to cloud data platforms such as Snowflake and Azure-based data services.
• Participate in code reviews and technical walkthroughs as a learning opportunity.
Collaboration & Communication
• Work closely with senior data engineers, analysts, and product owners to understand business and technical requirements.
• Support team activities such as sprint planning, backlog grooming, and sprint reviews in an Agile delivery model.
• Communicate progress, issues, and learnings clearly to mentors and team members.
Data Governance & Compliance
• Learn and adhere to data governance, security, and access control standards.
• Assist in implementing basic data validation, audit columns, and control checks required for enterprise and finance data.

• Undergraduate (or recent graduate) in Computer Science, Information Technology, Data Science, Engineering, or a related field.
Technical Skills (Basic / Foundational)

• Fundamental knowledge of SQL (SELECT, JOINs, basic aggregations).
• Basic programming knowledge in Python or a similar language.
• Understanding of relational databases and data concepts (tables, keys, data types).
• Familiarity with basic data engineering or analytics concepts is a plus.

• Strong willingness to learn and take feedback positively.
• Good analytical and problem-solving skills.
• Clear written and verbal communication skills.
• Ability to work collaboratively in a team environment.

• Exposure to cloud platforms (Azure, AWS, or GCP) in coursework or projects.
• Basic familiarity with Snowflake, Spark, or data integration tools (e.g., ADF) is an advantage but not mandatory.
• Academic or personal projects involving data pipelines or databases.
• Interest in finance or enterprise data domains.