YOUR SKILLS & ABILITIES (REQUIRED QUALIFICATIONS)

• 5+ years of hands-on experience delivering enterprise-scale data and analytics solutions using modern hybrid cloud technologies with a focus on data curation for Customer Experience data science modeling and reporting.
• Strong problem-solving and analytical skills with practical experience analyzing and curating large scale customer event data products from disparate data sources including 1st party and 3rd party data and map type data with variable structure.
• In-depth knowledge of industry-standard Data Engineering practices including data privacy & security, ETL/ELT, data architecture, data quality assurance, performance optimization, source code management, release management, and operations.
• Expert programming skills in data and analytics platforms, big data processing frameworks and languages, and development tools including Azure (or similar), Databricks, Spark, Python, SQL, and GitHub.
• Effective communication and people skills, with the ability to collaborate effectively with cross-functional technical teams and non-technical stakeholders.
• Naturally curious with the ability to work independently and proactively.
• Experience working in an Agile development environment.

EDUCATION

• Bachelor’s degree (or equivalent work experience) in Computer Science, Data Science, or a related field. Master’s degree is a plus.

WHAT WILL GIVE YOU A COMPETITIVE EDGE (PREFERRED QUALIFICATIONS):

• Experience with Salesforce data.
• Experience with Contact Center data.
• Experience with Customer Event data.
• Experience customer identity management platforms such as Amperity.
• At least one cloud certification in Azure.

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

• The salary range for this role is $93,400- $149,200. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more
GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE.

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THE ROLE

As a Senior Data Engineer, Applied Analytics & Insights (AA&I), you will play a crucial role in delivering future-focused, consumer-centric, prescriptive solutions that allow GM to stay proactive and nimble in our exciting transition to EVs. You will join the AA&I Analytics Engineering hub and will develop development of high-quality, scalable, and curated data products that power the AA&I Decision Science and Data Science portfolios. These portfolios serve several lines of business, including Loyalty, OnStar, Digital Services & Experience, and Growth Businesses. Additionally, you will collaborate with other AA&I Data Engineers and cross-functionally with partner teams to create a solid data engineering foundation.

WHAT YOU WILL DO

• Collaborate with the Decision Science and Data Science Innovation Hub functions in a matrixed reporting structure to develop data products for applied analytics solutions. Initial focus will be on Customer Experience use cases including Unified Customer Profiling & Identity Management, Clickstream Analytics, and Customer Engagement Insights.
• Design and develop data products that are compliant with data privacy and security policy to protect and manage sensitive data including customer data.
• Drive the adoption of cloud-first technologies and industry-standard Data Engineering practices to accelerate and scale engineering capabilities. Collaborate with cross-functional teams including data governance, data architecture, release management, Data Ops & ML Ops, and infrastructure as required.
• Stay up to date with emerging trends and technologies in the field of Data Engineering and proactively find opportunities for improvement and innovation within our organization.
• Foster a culture of continuous learning, knowledge sharing, and development within the team and the broader data engineering community.