Software Engineer – (Data Engineering)

  Clinical Research

Job title: Software Engineer – (Data Engineering)

Company: Apple

Job description: 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 Global Business Intelligence (GBI) team is seeking an experienced Data Engineer to build high quality, scalable and resilient distributed systems that power apple’s analytics platform and data pipelines. Apple’s Enterprise Data warehouse landscape caters to a wide variety of real-time, near real-time and batch analytical solutions. These solutions are integral part of business functions like Sales, Operations, Finance, AppleCare, Marketing and Internet Services, enabling business drivers to make critical decisions. We leverage a diverse technology stacks such as Teradata, HANA, Vertica, Hadoop, Kafka, Spark, Cassandra and beyond. Designing, Developing and scaling these big data technologies are a core part of our daily job. The ideal candidate for this position will be able think outside of the box and should have passion for building analytics solutions to enable our business partners to make time sensitive and critical decisions.

Key Qualifications Key Qualifications

  • In-depth understanding of data structures and algorithms
  • Experience in designing and building dimensional data models to improve accessibility, efficiency, and quality of data
  • Database development experience with Relational or MPP/distributed systems such as Oracle/Teradata/Vertica/HANA/Hadoop/ SingleStore/ SnowFlake
  • Programming experience in building high quality applications, data pipelines and analytics solutions. Experience in developing Big Data applications using java, Spark, Hive, Oozie, Kafka, and Map Reduce is a huge plus
  • 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
  • Exposure to cloud methodologies and experience with AWS or GCP.
  • Demonstrate strong understanding of development processes and agile methodologies
  • Strong analytical and communication skills. Should be self-driven, highly motivated and ability to learn quick
  • Familiarity with ML/AI technologies and methods like NLP, NLG, Automated Insights

Description Description

– Design and build data structures on MPP platform like Teradata, Hadoop to provide efficient reporting and analytics capability. Design solutions using new generation In-Memory Columnar databases like HANA. – Design and build highly scalable data pipelines using new generation tools and technologies like Spark, Kafka to induct data from various systems – Translate complex business requirements into scalable technical solutions meeting data warehousing design standards. Strong understanding of analytics needs and proactive-ness to build generic solutions to improve the efficiency. – Build dashboards using Self-Service tools like Tableau and perform data analysis to support business. – Collaborate with multiple cross functional teams and work on solutions which has larger impact on Apple business. Will work with global teams in US, Singapore and Europe. – You will work with many global teams, communicate effectively, both written and verbal, with technical and non-technical multi-functional teams. – You will interact with many other group’s internal team to lead and deliver elite products in an exciting rapidly changing environment. – Strong business understanding of Sales including Consumer and Enterprise markets. Knowledge in Operations and Finance area business process is a plus.

Education & Experience Education & Experience

Bachelor’s Degree or Equivalent with 6+ years of experience in data engineering field.

Expected salary:

Location: Hyderabad, Telangana

Job date: Wed, 20 Jul 2022 06:37:48 GMT

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