Senior Data Engineer

August 2024 - November 2024

Friday, November 1, 2024

As a senior data engineer at Axis I continued to expand my responsibilities and contributions to both Axis and clients.

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Description

I continued my progression at Axis Group as a senior data engineer. My new role blended project leadership, client engagement and technical abilities in a hands-on-keyboard role. The defining feature of my time as a senior engineer was an expectation of increased client collaboration and strategic thinking. Leveraging an increased understanding of the data landscape I created sustainable solutions that made the lives of our clients easier. I partnered closely with executives and technical stakeholders to define solutions, translated business objectives into scalable architectures, and ensured successful implementation in high-stakes environments. I specialized in:

  • Machine Learning modeling to continuously extract value from seemingly dormant data sources
  • Architect data platforms that integrated with existing systems
  • Best practices for onboarding of new tools

One of the most significant projects I led involved the inventory management system of a Fortune 500 company. My team was tasked with re-imagining how each location considers supply levels, discrepancies and pricing. I architected the data ingestion and analysis processes, partnered with executives to create a unified data strategy and implement the vision created. The project resulted in $20 million dollars of savings for the client and visibility into $67 million dollars worth of merchandise.

Beyond individual contributions, I piloted internal initiatives and knowledge to benefit the larger Axis organization. My role also required developing complex, business-critical solutions independently when timelines were tight or requirements were ambiguous, reinforcing my ability to deliver under pressure. Over the course of multiple engagements, I became a recognized subject matter expert in distributed data systems, Spark, and machine learning workflows—trusted by both clients and internal leadership for technical direction and strategic guidance.

Responsibilities

  • Own and create data projects including but not limited to:
    • Data Strategy
    • Supervised and Unsupervised machine learning
    • Data Science
    • Machine Learning modeling
  • Lead client engagements
  • Own internal knowledge gathering and tooling initiatives

Projects

Talks

Lessons Learned

  • The most technically brilliant solution is not guaranteed to be the final solution