Lead Data Governance Engineer

Lead Data Governance Engineer

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The Data Governance team is looking for a passionate, self-motivated and hard-working engineer to be part of a diverse, fast paced and high-energy team. We are seeking a Data Governance Engineer to build high-quality, scalable, and resilient distributed systems that power the analytics platform and data pipelines. As a key player in our data initiatives, you will be instrumental in defining and delivering robust cloud-based analytical and big data solutions that drive significant business impact.

Description

As a Data Governance Engineer, you'll be part of a team responsible for establishing and maintaining robust data governance frameworks, policies, and standards across Apple. You'll collaborate with various teams to drive data governance initiatives forward. At the forefront of your role will be designing and building innovative data and analytics solutions to meet Apple's complex business needs. You'll design and develop executive reporting solutions to mitigate data governance risks across the company. Additionally, you'll identify and resolve data discrepancies to create actionable visualizations that inform decision-making. Collaboration with cross-functional teams is crucial to enable business units and teams to embed data governance principles into operational processes and systems. Your ultimate goal is to develop comprehensive governance solutions that ensure the integrity, privacy, and security of Apple's diverse data assets.

Minimum Qualifications

Experience as a Data Engineer or similar role with experience in data governance, data management, aggregating data sources, metric definition, data visualisation with tools like Tableau or Apache Superset. Experience using SQL, Spark/PySpark, Python, Java, or Scala Strong understanding of data privacy regulations (e.g., GDPR, EU AI Act, CCPA) and industry best practices. BS in Computer Science, Mathematics, Statistics or equivalent experience.

Preferred Qualifications

Proficiency in designing and developing custom ETL pipelines using SQL and scripting languages (Python/Shell) and workflow management tools like Airflow. Proficiency in SQL within MPP/distributed databases like Apache Druid, Snowflake and Redshift in large-scale environments. Proven data driven decision making skills Experience in deploying large-scale streaming data pipelines using Kafka and Spark. Proficiency in advanced SQL and performance tuning. Experience with Snowflake AI features like, Cortex and DocAI, for using machine learning and document processing to improve data workflows and insights. Experience in backend API development and management using Java, Scala, or Python. Experience with version control systems, CI/CD practices, automated testing, and migration tools for databases and software Experience with Kubernetes and Docker Experience with reporting tools like Tableau, Apache Superset and QuickSight