Senior Data Analyst

Our Engineering Culture:

In our Agile/Lean DevOps environment, we've nurtured a culture of innovation and experimentation across our development teams. As a customer-focused organization, we collaborate closely with our end users and product owners to understand and rapidly respond to emerging business needs. Collaboration is ingrained into every aspect of our work – from the products we develop to the world-class service we offer. We are motivated by the belief that diversity of thought, background, and perspective is crucial to crafting the finest products and experiences for our customers. Come join us and become a part of a highly ambitious team dedicated to delivering impeccable solutions!

What You'll do

As a Senior Data Analyst at Principal Financial Group, you will play a key role in helping the business make data-driven decisions. You will work with large and complex data sets to identify trends, patterns, and insights that address business challenges and opportunities. 

You'll have opportunity to:

• Performing general analytics, statistical modeling on data sets in various areas of the business.
• Activities include data aggregation and insight development, analysis of data and presentation.
• Examines and identifies data patterns and trends to help answer business questions and improve decision making.
• A Senior Professional applies advanced knowledge of job area typically obtained through education and work experience.
• Managing projects / processes, working independently with limited supervision.
• Problems faced are difficult and sometimes complex. Coaching and reviewing the work of lower level professionals.

Who You are: 

Education: Bachelor Degree in engineering , Masters Degree in Statistics: Business or Technical with exposure to statistics as a subject

Experience: 4 to 7 Years

5-7 years of related analytics, consulting, project management, or equivalent experience preferred

•  Hands on experience on working on moderate to high volume data using statistical tools
• Ability to derive basic statistics like mean, median, test of hypothesis, etc.
• Business intelligence applications and/or cloud services (e.g., Alteryx, PowerBI, Qlik, Tableau). 
• Data querying, transformation, and processing languages such as SQL, Python, Power BI DAX/M Query, or SAS. 
• Operational, enterprise, and analytical relational/non-relational data stores such as PaaS cloud technologies, SQL Server, Oracle, and DB2. 
• Knowledge of cloud platforms and surrounding ecosystems (AWS, Azure).