A Day in the Life of a Data Analyst at AWS

Kang’s role at AWS is multifaceted, encompassing responsibilities of a business analyst, data engineer, and data analyst. “At AWS, our goal is to track metrics and see how the business is performi...
A Day in the Life of a Data Analyst at AWS
Written by Rich Ord
  • As the clock strikes 9:45 AM, Agatha Kang, a Business Intelligence Engineer at Amazon Web Services (AWS), begins her day. The office is still quiet, a perfect setting for what promises to be a busy day filled with operational meetings and data projects. Kang’s role at AWS is multifaceted, encompassing responsibilities of a business analyst, data engineer, and data analyst. “At AWS, our goal is to track metrics and see how the business is performing, and all of this is done through data,” she explains.

    Kang’s journey into the tech world is as intriguing as her current role. She spent six years as a data analyst in healthcare before making a significant career pivot. “I loved mentoring people when I got promoted to manager of data analytics in healthcare, but I missed being hands-on with data,” Kang shares. “Healthcare operates at a slower pace, and I wanted more of a challenge, which I found at Amazon. The pace here is a lot faster, and the work is very challenging, but that’s what I enjoy.”

    The Experiment Begins

    Kang’s typical day involves a heavy use of SQL along with tools like Excel, Python, and BI visualization tools. Her primary collaborators are the planning teams, who rely on her to build data solutions that automate their manual work and enable data-driven decisions. “Most of my day is spent using SQL, but I also use other tools like QuickSight and cloud technologies. My work helps the planning teams make better decisions based on data,” Kang explains.

    At 10:00 AM, Kang joins an operational meeting where her team discusses on-call tickets and any ad hoc work that needs to be addressed. These meetings are vital for brainstorming and sharing ideas on how to improve their data processes. “Working with smart people who have more data experience than I did initially was challenging, but I’ve learned so much from my team,” Kang says. “These operational meetings are super helpful for us to collaborate and find better ways to build our solutions.”

    Broadening Horizons: Sectors Embracing AI

    Kang’s work spans various sectors, reflecting the broad applicability of AI and data analytics. “In my role, I’ve worked on projects for different industries including healthcare, manufacturing, aerospace, telecommunications, and consumer packaged goods,” Kang notes. This diversity keeps her job interesting and continuously pushes her to learn new technologies. “Being in tech means dealing with complex problems, and that’s what makes it so rewarding. Each sector has its unique challenges, but the principles of data analysis remain the same.”

    Federal Government: A Major Growth Driver

    Public sector projects have become a significant part of Kang’s portfolio, especially with the federal government’s increasing reliance on data analytics for efficiency and optimization. “The federal government has doubled its investment in AI and data analytics, particularly in defense and intelligence,” Kang explains. “We work on projects that optimize logistics, supply chains, and even predictive maintenance for aircraft. The goal is to leverage data to enhance operational efficiency and decision-making capabilities.”

    Enterprise Software and AI: A Synergistic Relationship

    The integration of AI with enterprise software has transformed how businesses operate, and Kang’s role at AWS places her at the forefront of this evolution. “Enterprise software is a massive industry, and traditional technology stacks are being revolutionized by AI,” Kang states. “These AI-driven applications allow companies to predict customer behavior, prevent supply chain disruptions, and maintain complex infrastructures like the power grid or oil and gas networks.”

    Adapting to New Pricing Models

    Kang’s team has also adapted to new business models to meet customer needs better. “We transitioned from a subscription model to a pay-as-you-go model a couple of years ago,” she explains. “This change has increased our revenue growth because it allows clients to scale their usage based on their needs. It’s more flexible and aligns better with how businesses want to manage their costs.”

    Navigating a Transformative Landscape

    As the day winds down, Kang reflects on her decision to switch from healthcare to tech and the journey so far. “I’ve never looked back since making the move. The fast-paced environment and the opportunity to solve complex problems with smart people make every day exciting,” she says. For those considering a career in tech, Kang offers this advice: “Embrace the challenges and keep learning. The tech industry is constantly evolving, and staying curious is key to success.”

    Kang’s day may end at the office, but her passion for data and technology continues to drive her forward. “The work we do at AWS not only impacts the company but also shapes the future of data analytics and AI. It’s a privilege to be part of such a transformative journey.”

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