Software Engineer

About the Role

We are seeking a strong and passionate software engineer with experience in large scale system implementation, with a focus on complex data pipelines. The candidate must be able to design and drive large projects from inception to production. The right person will work with stakeholders, analysts, scientists to gather requirements and translate them into a data engineering roadmap. Must be a great communicator, team player, and a technical powerhouse.

What the Candidate Will Need / Bonus Points - What the Candidate Will Do -

Collaborate with engineering/product/analyst teams across tech sites to collectively accomplish OKRs to take Uber forward.

Enrich data layers to effectively deal with the next generation of products which are a result of Uber's big bold bets.

Design and build data pipelines to schedule & orchestrate a variety of tasks such as extract, cleanse, transform, enrich & load data as per the business needs.

Qualifications:

• Bachelor's degree in Computer Science, Software Engineering, or a related field.
• Proficiency in at least one programming language such as Java, Go, C++, etc.
• Strong SQL skills
• Strong in Data Warehousing and Data Modelling concepts

• Hands on experience in Hadoop tech stack:
• HDFS, Hive, Oozie, Airflow, MapReduce, Spark.
• Programming languages - Python, Java, Scala etc.
• Experience in building ETL Data Pipelines
• Performance Troubleshooting and Tuning
• Experience with DW (Data Warehouse) or BI (Business Intelligence) or OLAP tools like Anaplan, TM1, Hyperion etc.
• Experience building high-quality end-to-end data solutions in an agile environment from requirements to production.
• Strong in Data Warehousing concepts
• Should be self-motivated and passionate about bringing efficiency into the system through optimizations.
• Should be able to raise the bar for other engineers by proposing and driving innovative ideas.
• Experience in mentoring junior team members technically.
• If need be, Act as a Leader to drive big efforts in collaboration with other engineers or team members.

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

• Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.

- Basic Qualifications -

• Bachelor's degree in Computer Science, Software Engineering, or a related field.
• Proficiency in at least one programming language such as Java, Go, C++, etc.
• Strong SQL skills
• Strong in Data Warehousing and Data Modelling concepts

- Preferred Qualifications -

• Hands on experience in Hadoop tech stack:
• HDFS, Hive, Oozie, Airflow, MapReduce, Spark.
• Programming languages - Python, Java, Scala etc.
• Experience in building ETL Data Pipelines
• Performance Troubleshooting and Tuning
• Experience with DW (Data Warehouse) or BI (Business Intelligence) or OLAP tools like Anaplan, TM1, Hyperion etc.
• Experience building high-quality end-to-end data solutions in an agile environment from requirements to production.
• Strong in Data Warehousing concepts
• Should be self-motivated and passionate about bringing efficiency into the system through optimizations.
• Should be able to raise the bar for other engineers by proposing and driving innovative ideas.
• Experience in mentoring junior team members technically.
• If need be, Act as a Leader to drive big efforts in collaboration with other engineers or team members.