Lead Software Engineer

NikeBeaverton, OR
Remote

About The Position

Manage the coordination and overall integration of technical activities in engineering projects; direct, review or approve project design changes; assess project feasibility by analyzing technology, resource needs or market demand; develop or implement policies, standards, or procedures for engineering and technical work; establish technical goals within broad outlines provided by top management; direct recruitment, placement and evaluation of engineering project staff; extract meaning from data using specialized computer systems to transform, organize, and model the data to draw conclusions and identify patterns; use practical application of data collection and analysis to design, manage and optimize the flow of data throughout the organization; implement and execute strategies for a larger team (or multiple smaller teams) to deliver business results; solve complex problems using limited information; implements solutions taking into consideration future implications; work with non-routine information and develops recommendations to gain approval of ideas or services; accountable for meeting short-term to medium-term targets that impact the department or team; responsible for performance management, pay and resourcing decisions for direct reports; responsible for the team's delivery of scalable data solutions to solve a customer need; identify and solve enterprise issues concerning data management to improve data quality, and ensure the implementation of automated workflows, continuous integration, test-driven development and production deployment frameworks; guide the team in identifying and solving data issues and performing root-cause analysis to actively resolve product issues; and collaborate with other data engineers in the review of design, code and test plans in support of maintaining data engineering standards.

Requirements

  • Spark for Data Engineering including batch and streaming pipelines
  • Advance SQL including complex queries, performance optimization and Big Data management
  • Python for data processing and workflow orchestration
  • Informatica for building complex ETL pipelines
  • AWS services including S3, EMR, Aurora DB, EC2
  • Airflow for ETL pipeline orchestration
  • Snowflake for datawarehousing and Petabyte scale Data Lakes
  • Hive on Hadoop ecosystems
  • Unix programming
  • Data Architecture to support petabyte scale LakeHouse implementations
  • Data Modeling to support complex LakeHouse implementations and reporting solutions

Responsibilities

  • Manage the coordination and overall integration of technical activities in engineering projects
  • Direct, review or approve project design changes
  • Assess project feasibility by analyzing technology, resource needs or market demand
  • Develop or implement policies, standards, or procedures for engineering and technical work
  • Establish technical goals within broad outlines provided by top management
  • Direct recruitment, placement and evaluation of engineering project staff
  • Extract meaning from data using specialized computer systems to transform, organize, and model the data to draw conclusions and identify patterns
  • Use practical application of data collection and analysis to design, manage and optimize the flow of data throughout the organization
  • Implement and execute strategies for a larger team (or multiple smaller teams) to deliver business results
  • Solve complex problems using limited information
  • Implement solutions taking into consideration future implications
  • Work with non-routine information and develop recommendations to gain approval of ideas or services
  • Accountable for meeting short-term to medium-term targets that impact the department or team
  • Responsible for performance management, pay and resourcing decisions for direct reports
  • Responsible for the team's delivery of scalable data solutions to solve a customer need
  • Identify and solve enterprise issues concerning data management to improve data quality, and ensure the implementation of automated workflows, continuous integration, test-driven development and production deployment frameworks
  • Guide the team in identifying and solving data issues and performing root-cause analysis to actively resolve product issues
  • Collaborate with other data engineers in the review of design, code and test plans in support of maintaining data engineering standards
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