Cloud Data Engineering Manager
The people here at Apple don’t just build products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it. Imagine what you could do here.
Are you passionate about handling large & complex data problems, want to make an impact and have the desire to work on groundbreaking big data technologies? Then we are looking for you.
At Apple, great 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. Would you like to work in a fast-paced environment where your technical abilities will be challenged on a day-to-day basis? If so, Apple's Business Intelligence team is looking for passionate, detail-oriented, technical savvy, energetic leader who like to think outside the box. Someone who is self motivated and ready to lead team of most talented engineers building high quality, scalable and resilient distributed systems that power apple's analytics platform and data pipelines.
AiDP (Artificial Intelligence and Data Platform) team deals with petabytes of data catering to a wide variety of real-time, near real-time and batch analytical solutions. These solutions are integral part of business functions like Anti Fraud, Retail, Sales, Operations, Finance, AppleCare, Marketing and Internet Services, enabling business drivers to make critical decisions. We leverage a diverse technology stack such as Snowflake, Spark, HANA, SingleStore, Kafka, Iceberg, Cassandra and beyond. Designing, developing and scaling these big data solutions are a core part of our daily job.
- Lead Data Warehouse/Business Intelligence development team in building Analytics solutions
- Lead the design for database and data pipeline/ETL using emerging technologies and tools
- Lead the reporting and dashboarding solutions using innovative packaged and custom-built tools
- Drive the team to develop operationally efficient analytic solutions
- Manage resources/budget and partner with global functional and business teams. Manage multiple teams and projects
- Define standards & methodologies for Data Warehousing environment
- Design and build highly scalable data pipelines using new generation tools and technologies like AWS, Snowflake, Spark, Kafka to induct data from various systems
- Translate complex business requirements into scalable technical solutions meeting data warehousing design standards. Solid understanding of analytics needs and proactive-ness to build generic solutions to improve the efficiency
- Lead/Work with many global teams, communicate effectively, both written and verbal, with technical and non-technical multi-functional teams
- Lead and mentor people and plan their career growth and focus on creating a cohesive team environment
- Thrives in a dynamic environment, maintaining composure and a positive attitude.
- Experience in leading, hiring, developing and building data engineering team and providing them technical direction.
- Experience managing Annual performance reviews, setting SMART goals for team members and invested lead in team member career development.
- Experience working with cloud technologies and big data stack be it Amazon AWS, Snowflake, Microsoft Azure or Google GCP.
- Experience in designing and building dimensional data models to improve accessibility, efficiency and quality of data.
- Bachelor’s Degree or Equivalent with 10+ years of experience in data engineering, computer science or statistics field with at least 2+ years of experience in leadership/management
- Experience in building high quality applications, data pipelines and analytics solutions ensuring data privacy and regulatory compliance.
- Experience working with Business Stakeholders to understand requirements and ability to translate them into scalable and sustainable solutions.
- Should be proficient in writing Advanced SQLs, expertise in performance tuning of SQLs.
- Experience with data science and machine learning tools and technologies is a plus
- Demonstrate good understanding of development processes and agile methodologies
- Strong analytical and communication skills.
- Should be self-driven, highly motivated and ability to learn quickly and lead by example.