Data Engineering Manager

Read on to fully understand what this job requires in terms of skills and experience If you are a good match, make an application.

Summary

Posted : Oct 9, 2024

Weekly Hours : 40

Role Number : 200571109

Be inspired every day. We’re perfectionists. Idealists. Inventors. A job at Apple is one that requires a lot of you, but it’s also one that rewards forward-thinking and hard work.

None of us here at Apple would have it any other way! In this role, you’ll be a key leader in the design, development, and implementation of data engineering solutions within the Apple Channel Sales team.

You’ll oversee a team responsible for building and optimizing scalable data pipelines that support critical decision-making, sales performance, and business planning for the U.

S. Channel Sales team. As the Data Engineering Manager, you will work hands-on to architect and maintain robust data infrastructure, ensuring that data is easily accessible, reliable, and actionable.

You will collaborate closely with cross-functional teams, including data scientists, analysts, and product managers, to ensure that data solutions align with business needs and drive operational efficiency.

Additionally, you’ll lead efforts to enhance data quality, governance, and security, while continuously driving innovation in data processing and automation.

Your leadership will be essential in guiding the team towards creating scalable data solutions that support the organization’s growth and improve overall data capabilities.

We view inclusion and diversity as critical for innovation. That’s because we lead ambitious projects, the ones that benefit from different perspectives to drive innovation.

Description

• Lead and manage a team of data engineers to design, build, and maintain data pipelines, ensuring data is available and accessible to all stakeholders.
• Collaborate with Sales, data science, analytics, and product teams to understand data requirements and deliver on projects in a timely manner.
• Architect scalable and efficient data solutions using modern technologies and best practices. - Drive innovation and automation in data processes to optimize data flow, reduce latency, and improve data quality.
• Establish and maintain data infrastructure, ensuring scalability, reliability, and cost-efficiency. - Develop and enforce data governance policies, ensuring data integrity, security, and compliance with industry standards.
• Mentor and grow the team, fostering a culture of learning, continuous improvement, and collaboration. - Stay current with emerging technologies and trends in data engineering, providing recommendations for adopting new tools and practices where relevant.
• Ensure high availability of data systems through monitoring, alerting, and on-call rotations as necessary. - Keep up-to-date with the latest industry trends and technologies to ensure work remains cutting-edge.
• Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related field, or equivalent practical experience.
• 8+ years of experience in data engineering, with a focus on building and maintaining scalable data pipelines.
• 2+ years of experience directly managing data engineering teams.
• Proficiency in SQL and Python.
• Experience with ETL tools and frameworks such as Apache Spark, Airflow, or similar.
• Strong understanding of cloud platforms (e.g., AWS, Google Cloud, Azure) and data warehousing solutions (e.g., Redshift, Snowflake, BigQuery).
• Proven experience with databases (both relational and NoSQL) and data modeling.
• Experience solving large-scale data-related issues, implementing new governance processes, managing data integration / ETL challenges.
• Experience in managing projects related to data governance or operations, including planning, execution, and monitoring.
• Understanding of data security and privacy best practices.
• Excellent problem-solving and communication skills.

Preferred Qualifications

• Master’s degree in Computer Science, Engineering, or a related field.
• Familiarity with modern data architectures such as Data Lakes and Data Mesh.
• Experience with machine learning platforms and data science workflows.
• Proficiency in DevOps tools (e.g., Terraform, Docker, Kubernetes) for automating infrastructure as code.
• Experience working with hardware sales companies or consumer goods industry.
• Excellent communication and storytelling skills, able to inspire non-technical colleagues on value proposition and impact of data governance.
• Experience leveraging AIML and automation solutions to reduce data-related errors and drive scale.

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role.

The base pay range for this role is between $146,000 and $243,300, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs.

Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan.

You’ll also receive benefits including : Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition.

Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note : Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

More

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.

Learn more about your EEO rights as an applicant.

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