Sr Data Engineer
San Diego, California
Summary
The Software Delivery Data Engineering team is focused on improving build data transparency, facilitating data driven decisions to be made across Software Engineering. These cross-functional collaborations will drive actions to ensure software releases are shipped on time with quality features.
We collaborate with cross-functional teams to build up large-scale data pipelines, drive both description and predictive analysis, as well as visualize the data via various tools, frameworks, and services.
We're looking for a senior data engineer who has extensive working experience in delivering big data platforms or large-scale data pipelines or streaming systems in the public cloud. You'll be working on a unique and challenging big data ecosystem, building scalable data pipelines that process, clean, and validate the integrity of the data from raw sources based on engineering specifications and business intelligence for analytics use.
Key Qualifications
6+ years experience in architecting, designing, and developing large scale data solutions.
Deep understanding and strong development experience with distributed data processing frameworks such as Hadoop, Spark and others
6+ years experience in building and maintaining large-scale ETL/ELT pipelines (batching and/or streaming) that are optimized for performance and can handle data from various sources, structured or unstructured.
Proficiency in various data modeling techniques, such as ER, Hierarchical, Relational, or NoSQL modeling.
Excellent design and development experience with SQL and NoSQL database, OLTP and OLAP databases
Expertise in Python, Unix Shell scripting and Dependency driven job schedulers
Description
In this role, you will be collaborating with data scientists, data analysts, software developers, data engineers, and project managers to understand requirements and translate them into scalable, reliable, and efficient data pipelines, data processing workflows, and machine learning pipelines.
You will be responsible for architecting and implementing large scale systems and data pipelines with a focus on agility, interoperability, simplicity, and reusability. You should have deep knowledge in infrastructure, warehousing, data protection, security, data collection, processing, modeling, and metadata management, and able to build an end-to-end solutions that also support metadata logging, anomaly detection, data cleaning, transformation, etc.
The ideal candidate is a highly motivated, collaborative, and proactive individual who can communicate effectively and can adapt and learn quickly.
Education & Experience
Bachelor's or Master's degree in Computer Science, Information Systems, Software Engineering, Data Science, or a related field.
Additional Requirements
The Software Delivery Data Engineering team is focused on improving build data transparency, facilitating data driven decisions to be made across Software Engineering. These cross-functional collaborations will drive actions to ensure software releases are shipped on time with quality features.
We collaborate with cross-functional teams to build up large-scale data pipelines, drive both description and predictive analysis, as well as visualize the data via various tools, frameworks, and services.
We're looking for a senior data engineer who has extensive working experience in delivering big data platforms or large-scale data pipelines or streaming systems in the public cloud. You'll be working on a unique and challenging big data ecosystem, building scalable data pipelines that process, clean, and validate the integrity of the data from raw sources based on engineering specifications and business intelligence for analytics use.
Key Qualifications
6+ years experience in architecting, designing, and developing large scale data solutions.
Deep understanding and strong development experience with distributed data processing frameworks such as Hadoop, Spark and others
6+ years experience in building and maintaining large-scale ETL/ELT pipelines (batching and/or streaming) that are optimized for performance and can handle data from various sources, structured or unstructured.
Proficiency in various data modeling techniques, such as ER, Hierarchical, Relational, or NoSQL modeling.
Excellent design and development experience with SQL and NoSQL database, OLTP and OLAP databases
Expertise in Python, Unix Shell scripting and Dependency driven job schedulers
Description
In this role, you will be collaborating with data scientists, data analysts, software developers, data engineers, and project managers to understand requirements and translate them into scalable, reliable, and efficient data pipelines, data processing workflows, and machine learning pipelines.
You will be responsible for architecting and implementing large scale systems and data pipelines with a focus on agility, interoperability, simplicity, and reusability. You should have deep knowledge in infrastructure, warehousing, data protection, security, data collection, processing, modeling, and metadata management, and able to build an end-to-end solutions that also support metadata logging, anomaly detection, data cleaning, transformation, etc.
The ideal candidate is a highly motivated, collaborative, and proactive individual who can communicate effectively and can adapt and learn quickly.
Education & Experience
Bachelor's or Master's degree in Computer Science, Information Systems, Software Engineering, Data Science, or a related field.
Additional Requirements
- Capacity to translate business requirements into technical solutions.
- Experienced in writing and maintaining high-quality code using standard methodologies such as code reviews, unit testing, and continuous integration.
- Stay up-to-date with the latest trends and technologies in data infrastructure, architecture, big data analytics, and apply them to improve the system.
- Familiarity with other related fields, such as data science, machine learning, and artificial intelligence, to design solutions that can accommodate advanced analytics.
- Ability to identify and address issues in data design or integration.
- Collaborative mindset to work with various teams, including data engineers, data analysts, and cross functional partner teams.
- Good time management skills and can incrementally deliver to tight schedules.
Created: 2024-05-07
Reference: 200518299
Country: United States
State: California
City: San Diego
ZIP: 92109
About Apple
Founded in: 1976
Number of Employees: 154000
Website: https://www.apple.com/
Career site: https://www.apple.com/careers/us/
Wikipedia: https://en.wikipedia.org/wiki/Apple_Inc.
Instagram: https://www.instagram.com/apple/
LinkedIn: https://www.linkedin.com/company/apple
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