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Sr. Data Engineer

Capgemini

HybridHybrid

Original Job Summary

Sr. Data Engineer Job Description

Our client is one of the United States’ largest insurers, serving over 10 million U.S. households and managing more than 19 million policies. Part of one of the largest Insurance Groups globally, this role involves understanding, analyzing, and translating business data stories into technical story breakdowns.

As a Sr. Data Engineer, you will design, build, test, and implement data products with limited coaching. You will work with tools such as Excel, PowerPoint, Power BI, Python, and SQL, and will be involved with data architecture, data governance, data mining, and data visualization.

Core Responsibilities

  • Translate business data stories into technical solutions
  • Design and build systems for collecting, cleaning and processing data
  • Set blueprints for data architecture and flow
  • Implement data governance policies ensuring integrity and security
  • Utilize data visualization tools to support decision-making

Technical & Software Skills

  • SQL (Intermediate)
  • Informatica (Intermediate)
  • Power BI (Entry Level)
  • Python (Entry Level)
  • SHELL/Linux Scripting (Entry Level)
  • ETL Integration Tools (Intermediate)
  • Snowflake (Intermediate)
  • AWS (Intermediate)

Other Requirements & Benefits

  • Fluent English and a Bachelor's degree in Engineering, Mathematics, or related
  • 7 to 9 years of relevant work experience
  • Competitive salary with performance-based bonuses
  • Comprehensive benefits including health insurance, pension plan, and paid time off
  • Flexible work arrangements: remote and/or office-based

Key skills/competency

  • Data Analytics
  • Data Architecture
  • Data Governance
  • Data Mining
  • Data Visualization
  • SQL
  • Python
  • ETL
  • Snowflake
  • AWS

How to Get Hired at Capgemini

🎯 Tips for Getting Hired

  • Research Capgemini's culture: Study mission, values, and recent news.
  • Customize your resume: Tailor skills to match data engineering requirements.
  • Showcase technical projects: Emphasize SQL, Python, and ETL experience.
  • Prepare for interviews: Highlight problem-solving and collaboration stories.

📝 Interview Preparation Advice

Technical Preparation

Review SQL, ETL, and cloud integration basics.
Practice Python scripting and data transformation tasks.
Study Snowflake and AWS best practices.
Refresh knowledge on data governance and architecture.

Behavioral Questions

Describe a challenging data project you led.
Explain your collaboration during technical problem-solving.
Share an experience handling tight deadlines.
Demonstrate how you adapt to changing requirements.