Data Engineering Apprentice

Responsibilities

• Job Summary
• 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.
• 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.

Requirements

• 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.

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Company Intel

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