Data Engineering Apprentice

## What you\u2019ll do:\n\nJob Summary \nThe 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. \nThe 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.\n\nKey Responsibilities \nData Engineering \u0026 Platform Support \n\u2022 Assist in building and maintaining data pipelines for ingesting, transforming, and validating data from various source systems. \n\u2022 Support data transformations using SQL and Python under established engineering standards. \n\u2022 Help with data quality checks, reconciliation processes, and basic troubleshooting of data issues. \n\u2022 Participate in documenting data pipelines, table definitions, and engineering artifacts. \nLearning \u0026 Engineering Practices \n\u2022 Learn and apply modern data engineering practices including ELT/ETL pipelines, version control, and CI/CD fundamentals. \n\u2022 Follow enterprise data engineering standards for naming conventions, data modeling, and code quality as defined by the team. \n\u2022 Gain hands-on exposure to cloud data platforms such as Snowflake and Azure-based data services. \n\u2022 Participate in code reviews and technical walkthroughs as a learning opportunity. \nCollaboration \u0026 Communication \n\u2022 Work closely with senior data engineers, analysts, and product owners to understand business and technical requirements. \n\u2022 Support team activities such as sprint planning, backlog grooming, and sprint reviews in an Agile delivery model. \n\u2022 Communicate progress, issues, and learnings clearly to mentors and team members. \nData Governance \u0026 Compliance \n\u2022 Learn and adhere to data governance, security, and access control standards. \n\u2022 Assist in implementing basic data validation, audit columns, and control checks required for enterprise and finance data.\n\n## Qualifications:\n\n \n\u2022 Undergraduate (or recent graduate) in Computer Science, Information Technology, Data Science, Engineering, or a related field. \nTechnical Skills (Basic / Foundational)\n\n## Skills:\n\n\u2022 Fundamental knowledge of SQL (SELECT, JOINs, basic aggregations). \n\u2022 Basic programming knowledge in Python or a similar language. \n\u2022 Understanding of relational databases and data concepts (tables, keys, data types). \n\u2022 Familiarity with basic data engineering or analytics concepts is a plus.\n\n\u2022 Strong willingness to learn and take feedback positively. \n\u2022 Good analytical and problem-solving skills. \n\u2022 Clear written and verbal communication skills. \n\u2022 Ability to work collaboratively in a team environment.\n\n \n\u2022 Exposure to cloud platforms (Azure, AWS, or GCP) in coursework or projects. \n\u2022 Basic familiarity with Snowflake, Spark, or data integration tools (e.g., ADF) is an advantage but not mandatory. \n\u2022 Academic or personal projects involving data pipelines or databases. \n\u2022 Interest in finance or enterprise data domains.\n