Services Finance Data Engineer

Apple • Cupertino, CA

2d

About The Position

Services Finance Data Science and Engineering team is looking for a passionate
and highly motivated Data Engineer to drive our financial data platform forward.
You will provide a key function in shaping the success of Apple’s current and
future products. As members of the Services Finance Data Science and Engineering
team, we work with various business and engineering teams to understand current
and future business initiatives. We need to be persistent and flexible in
extracting data from various sources, cleaning and curating this data, and then
clearly and concisely communicating insights.

The individual in this role will collaborate with data scientists, business
analysts and subject matter experts (SME) to acquire, and transform raw data and
develop sophisticated data products. This includes developing and maintaining
data pipelines, extracting from different sources (databases, APIs, etc.), and
transforming raw data into normalized tables after running data quality checks.
A successful data engineer is skilled in taking a business problem and
translating it into a data solution in close collaboration with data scientists,
business analysts, and SMEs.

Requirements

• Minimum of 5 years of working experience as a data engineer building end-to-end data pipelines
• Advanced SQL skills for complex transformations, optimization, and troubleshooting
• A Bachelor’s degree in Statistics, Computer Science, Computer Engineering, or equivalent practical experience
• Python proficiency, comfortable writing clean, maintainable Python for data pipelines and automation
• Hands-on experience working with relational database management system such as Snowflake, PostgreSQL or similar cloud data warehouses
• Ability to work both independently and within a team environment
• Strong written and verbal communication skills, capable of explaining technical results to a non-technical audience

Nice To Haves

• Experience with scheduling systems and CI/CD tools such as Airflow, Jenkins, etc.
• Understanding of dimensional modeling, data warehousing concepts, medallion and data lakehouse architectures
• Hands-on experience with building ETL process and writing unit tests using DBT or similar tools

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees