Data Engineer - Wallet Payments & Commerce

Austin, Texas, United States
Software and Services


Role Number:200157761
Looking for skilled, hardworking and results-oriented individuals to join our team to build data foundations to craft the future of commerce and Apple Pay. You will design and implement scalable, extensible and performant data pipelines and data structures on large volume data sets, that will enable actionable insights & strategy for payment products. Our culture is about getting things done iteratively and rapidly, with open feedback and debate along the way. We believe analytics is a team sport, but we strive for independent decision-making and taking smart risks. Our team collaborates deeply with partners across product and design, engineering, and business teams: our mission is to drive innovation by providing the business and data scientist partners outstanding systems and tools to make decisions that improve the customer experience of using our services. This will include demonstrating large and complex data sources, helping derive measurable insights, delivering dynamic and intuitive decision tools, and bringing our data to life via amazing visualizations. Working with the head of Wallet Payments & Commerce Data Engineering & BI, this person will collaborate with various data analysts, instrumentation specialists and engineering teams to identify requirements that will derive the creation of data structures and pipelines. You will work closely with the application server engineering team to understand the architecture and internal flows & APIs involved in upcoming and ongoing projects related to Apple Media Products and Apple Pay. We are seeking an outstanding person to play a pivotal role in helping the analysts & business users make decisions using data and visualizations. You will partner with key partners across the engineering, analytics & business teams as you design and build query friendly structures. The ideal candidate is a self-motived teammate, skilled in a broad set of Data modeling and processing techniques with the ability to adapt and learn quickly, provide results with limited direction.

Key Qualifications

  • 5+ years of professional experience with Data systems, Data schema, data pipelines
  • Practical hands-on experience with Teradata and SQL friendly data warehouses.
  • Expertise in data modeling, data schema design and implementation
  • Experience in translating the business requirements to a data model that is scalable
  • Expertise in ANSI SQL, Triggers and Procedures
  • Ability to understand API Specs, identify relevant API calls , extract data and implement data pipelines & SQL friendly data structures
  • Identify and implement Data Validation rules and alerts based on data publishing specifications for data integrity and anomaly detection
  • Expertise in Python, Unix Shell scripting and Dependency driven job schedulers
  • Expertise in Oracle, Teradata and Snowflake
  • Familiarity with rule based tools and APIs for multi stage data correlation on large data sets is a plus


- Translate business requirements by business team into data and engineering specifications - Build scalable data sets based on engineering specifications from the available raw data and derive business metrics/insights - Work with engineering and business partners to define and implement the data engagement relationships required with partners - Understand and Identify server APIs that needs to be instrumented for data analytics and reporting and align the server events for execution in already established data pipelines - Explore and understand complex data sets, identify and formulate correlational rules between heterogenous data sources for effective analytics and reporting - Process, clean and validate the integrity of data used for analysis - Develop Python and Shell Scripts for data ingestion from external data sources for business insights - Work hand in hand with the DevOps team and develop monitoring and alerting scripts on various data pipelines and jobs

Education & Experience

Minimum of bachelor’s degree, preferably in Computer Science, Information Technology or EE, or relevant industry experience is preferred

Additional Requirements