Senior Data Engineer at Capgemini designing and optimizing scalable data architectures on Databricks and GCP. Collaborating across teams to transform business needs into reliable technical solutions.
About the role
- Data Engineer transforming legacy on-premises systems to cloud-native architectures for advanced data analytics. Collaborating with teams to build efficient data solutions using Python and AWS.
Responsibilities
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver tailored data solutions
- Develop efficient data processing and transformation workflows to support analytics and reporting needs
- Design, build, and maintain data pipelines and automated extract, transform, load (ETL) processes using tools like Python, R, and platform‑specific environments such as Jupyter Notebooks
- Integrate disparate structured and unstructured data from APIs, databases, and cloud storage into unified datasets utilizing ETL patterns, frameworks, query techniques
- Implement processes for data cleaning, transformation, and validation to ensure data accuracy, consistency, and compliance with security and privacy policies
- Develop dashboards, visualizations, and analytical products leveraging QuickSight or other mission‑approved tools to support operational decision‑making
- Provide full lifecycle assistance in deploying, optimizing, maintaining complex code with data processing routines running in development, test, and production
- Optimize code through advanced algorithmic concepts to facilitate more efficient
Requirements
- 5+ years of experience as a Data Engineer, Data Scientist, or Backend Software Engineer
- Bachelor’s degree from an accredited college or university with a major in computer science, statistics, mathematics, economics, or related field
- Strong skills in Python and SQL and proficiency with other data engineering languages (e. g., R, SAS, SCALA)
- Proficient in handling large-scale data projects involving data integration, cleaning, ETL, analysis, aggregation, tabulation, and reporting
- Experience developing and implementing data reliability, efficiency, and quality checks and processes
- Experience leveraging AWS services (e.g., S3, EMR, Glue, Lambda, Athena, Redshift, SageMaker, QuickSight) to build and deploy data solutions in a cloud-native environment
- Experience with structured and unstructured data databases including Oracle, PostGreSQL, MySQL, Athena, Redshift, MongoDB etc.
- Familiarity with demographic, economic, and geospatial data sources and structures
- Experience working in an Agile organization using Scrum, Kanban, Jira, Confluence, and SAFe
- Excellent communication and teamwork skills
- Strong skills preparing and presenting design/architectural documents to clients
- Requires a Public Trust - must be US Citizen to be eligible.
Benefits
- Medical Insurance
- Vision Insurance
- Dental Insurance
- Life and AD&D Insurance
- 401(k) Savings Plan
- Education and Professional Training
- Flexible Spending Accounts (FSA)
- Employee Referral and Merit Recognition Programs
- Employee Assistance and Identity Theft Protection
- Paid Holidays: 11 per year
- Paid Time Off (PTO)
- Disability Insurance
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Data Engineering Academy focused on Snowflake and Databricks for professionals interested in expanding their technical capabilities. Fully remote with future office work in Monterrey or Saltillo after completion.
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