Azure Databricks Data Engineering Lead (17305-1) Seattle, WA

About the role

Azure Databricks Data Engineering Lead (17305-1) Seattle, WA

Experience level: Mid-senior Experience required: 7 Years Education level: Bachelors degree Job function: Information Technology Industry: Information Technology and Services Pay rate : Total position: 1 Relocation assistance: No Visa sponsorship eligibility: No

Job Description

7+ years of experience in Databricks, Microsoft Azure, PySpark and Python.
Lead large-scale, complex, cross-functional projects to build the technical roadmap for the WFM Data Services platform.
Lead and review design artifacts.
Build and own the automation and monitoring frameworks that showcase reliable, accurate, easy-to-understand metrics and operational KPIs to stakeholders for data pipeline quality.
Execute proof of concept on new technology and tools to pick the best tools and solutions.
Support business objectives by collaborating with business partners to identify opportunities and drive resolution.
Communicate status and issues to Senior Starbucks leadership and stakeholders.
Direct project team and cross-functional teams on all technical aspects of the projects.
Lead with engineering team to build and support real-time, highly available data, data pipeline and technology capabilities.
Translate strategic requirements into business requirements to ensure solutions meet business needs.
Define and implement data retention policies and procedures.
Define and implement data governance policies and procedures.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
Enable team to pursue insights and applied breakthroughs, while also driving the solutions to Starbucks scale.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of structured and unstructured data sources using big data technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Perform root cause analysis to identify permanent resolutions to software or business process issues.

Additional Notes:

Please submit the candidate's resume in PDF format.
Please remove the candidate's LinkedIn URL from the resume; otherwise, the profile will not be considered.
Please note that TCS does not consider former full-time employees (FTEs) for rehire. Additionally, individuals who have previously worked at TCS as contractors must observe a minimum waiting period of six months before being eligible for re-engagement.