Senior Data Engineer, Converse Technology (Open to Atlanta, Beaverton, Boston location)

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Nike

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There are 3 Senior Data Engineer positions available.

WHO YOU’LL WORK WITH

You will report to the Data Engineering Manager and work hand-in-hand with the data engineering squad and product management team along with a variety of dedicated Converse and Nike partners focused on technology solution delivery, architecture, and platforms. You will join a highly motivated, global team that will be a driving force in building Data and Analytic solutions for the Converse Enterprise.

WHO WE ARE LOOKING FOR

We are open to candidates in Atlanta, Beaverton or Boston area.

We are looking for someone who thrives in the ever-evolving world of data & analytics. The right candidate can quickly pick up new programming languages, technology concepts, and frameworks. They have strong problem-solving skills and an understanding of data structures and algorithms. They thrive in a hard-working team environment and have an ability to both influence and communicate effectively with team members and business stakeholders alike.

  • Bachelor’s degree or equivalent combination of education, experience or training
  • Minimum 5 years relevant work experience
  • Experience with data modeling, warehousing and building ETL pipelines; Must
    have experience with any ETL tools, preferably Matillion
  • Experience with SQL and scripting languages such as Python, Shell
  • Experience building cloud scalable, real-time and high-performance data lake
    solutions, preferably Databricks, Snowflake, AWS
  • Experience with source control tools preferred GitHub or Jenkins, terraform
  • Experience with big data technologies such as: Hadoop, Hive, Spark, EMR and
    orchestration tools like Airflow
  • A passion for data solutions and winning as a team

WHAT YOU’LL WORK ON

As a Senior Data Engineer on the Enterprise Data & Analytics team, you will drive work to completion with hands-on development responsibilities, and partner with the Lead Engineers to deliver quality components of a data product. You will build reusable components of a larger data pipeline to support data analytics products with guidance from experienced peers, all while working within an agile framework that focuses on delivering incremental value.

  • Design and build reusable components of a larger process or framework to support analytics products with guidance from experienced peers
  • Design and implement simple product features in collaboration with business and Technology stakeholders
  • Clean, prepare and optimize data for ingestion and consumption
  • Support the implementation of new data management projects and re-structure of the current data architecture
  • Implement simple automated workflows using workflow scheduling tools, such as Matillion or Brickflow
  • Understand and use current continuous integration, test-driven development and production deployment frameworks
  • Participate in design, code and test plan reviews to increase knowledge and application of best practices
  • Analyze and profile data for the purpose of designing components of a scalable solution
  • Troubleshoot straightforward data issues and perform root cause analysis to resolve product issues

We are committed to fostering a diverse and inclusive environment for all employees and job applicants. We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Category: Engineering Jobs

Tags: Agile Airflow Architecture AWS Big Data Data Analytics Databricks Data management Engineering ETL GitHub Hadoop Jenkins Matillion Pipelines Python Snowflake Spark SQL TDD Terraform

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