Data Engineer II, India – Consumer Services ICC
NIKEBangaloreUpdate time: December 17,2020
Job Description
Consumer Services has a number of call centers around the world. We are consumer’s first line contact when they need to contact Nike for any issues or concerns. The Consumer Service Data Warehouse collects inputs from the Consumer Services application eco-system and delivers this data in a modeled form utilization by the Consumer Services Analytic team to provide dashboards and reports to manage the business.
WHO WE ARE LOOKING FOR
- We’re looking for a well technically skilled and articulate Data Engineer II to join our team with at least 8+ years of industry experience.
- This role will perform a number of various tasks mainly developing and maintaining data pipelines from a number of different data sources.
- The candidate needs to have experience in ETL using a various data warehousing programming and technical tools
- Help train and mentor Data Engineer I with a number of technologies.
WHAT YOU WILL WORK ON
If this is you, you’ll be working with a team of 1 other engineer and 6 others at WHQ performing the following tasks:
- Build and implement data pipelines from a number of disparate data sources
- Maintaining existing data pipelines and troubleshoot any technical platform issues
- Analyze and profile data for the purpose of designing scalable solutions
- Mentor and develop other data engineers in adopting best practices
- Troubleshoot complex data issues and perform root cause analysis to proactively resolve product issues
- Help maintain and prioritize technical backlog
A typical day/week looks like (examples of “day in the life” tasks)
- Attend daily stand ups
- Work through the stories and ensure deliverables are met by the end of the two week sprint
- Mentor other engineers and provide simple solutions
- Attend product and technical refinement sessions. Help maintain the technical backlog by looking for long term proactive solutions with the processes
- Collaborate with other Nike teammates to understand requirements and deliverables
- Troubleshoot adhoc quick issues
WHO YOU WILL WORK WITH
You will be reporting to the Engineering manager, you will work with Product Manager, other Engineering Team Members and with a variety of talented Nike teammates. You will be part of team that will be a driving force in building ETL processes for Consumer Services Nike Technology.
WHAT YOU BRING
- 8+ years of industry experience and 8+ years of relevant big data/ETL data warehouse experience building data pipelines
- 5+ years leading a team of data engineers – ie mentor, improve processes, peer training, long term best practices, coding standards
- 6+ year experience in Python and Snowflake. Strong programming experience in Python
- Professionally worked with APIs to extract data for data pipelines
- Extensive experience working with Hadoop and related processing frameworks such as Spark, Hive, Sqoop, etc.
- Ability to architect, design and implement solutions with AWS Virtual Private Cloud, EC2, AWS Data Pipeline, AWS Cloud Formation, Auto Scaling, AWS Simple Storage Service, EMR and other AWS products, HIVE, Athena
- Troubleshooting production issues and performing On-Call duties, at times.
- Working knowledge with workflow orchestration tools like Apache Airflow
- Hands on experience with performance and scalability tuning
- Professional experience in Agile/Scrum application development using JIRA
- Experience working in a public cloud environment, particularly AWS
- Professional experience with source control, merging strategies and coding standards, specifically Bitbucket/Git
- Professional experience in data design, modeling, and being able to interpret STTMs
- Demonstrated experience developing in a continuous integration environment using tools like Jenkins, Bamboo, or TeamCity CI Frameworks.
- Demonstrated ability to maintain the build and deployment process through the use of build integration tools
- Working experience and communicating with business stakeholders and architects
- Demonstrated experience implementing security around sensitive data
- Experience designing instrumentation into code and using and integrating with software
- and logging analysis tools like log4Python, Signal FX and/or Splunk
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