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Capgemini

Data Engineer

Capgemini

. Acquire, curate, and publish data on premises and in the cloud for analytical or operational use .

Posted 10/13/2026full-timeHyderabad • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in data acquisition, curation, and publishing for analytical and operational use, with a strong focus on data governance and building scalable data pipelines. Proficient in translating business analytics into technical tasks while applying intermediate insurance domain knowledge.

Highest-signal resume keywords
AWS ExperienceDBT ExperienceSnowflake ExperienceData Analysis & ProfilingSQL and Python Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data Architecture & ModellingData MappingNatural Language ProcessingData TransformationStatistical ComputationData ValidationData Building BlocksData ModelsData FlowsAPI Integrations
Soft Skills
Project ManagementConsultationCollaboration
Tools & Technologies
AirflowVisualization ToolsAI/ML Tools
Industry Keywords
Intermediate Insurance Domain KnowledgeProperty & Casualty Insurance Knowledge

Tech Stack

Tools & technologies
AirflowAWSCloudPythonSQL

About the role

Key responsibilities & impact
  • Acquire, curate, and publish data on premises and in the cloud for analytical or operational use
  • Ensure data is ready to use and provides a single version of truth across data consumers
  • Translate business analytics requests into design, development, testing, deployment, and production maintenance tasks
  • Consult on intermediate-complexity data projects and lead design, development, and implementation of data products
  • Apply code management and data governance guidelines
  • Produce data building blocks, data models, and data flows for reporting, dashboards, data feeds, and data science
  • Create business-user access methods for structured and unstructured data
  • Apply data mapping, natural language processing, data transformation, AI, statistical computation, and data validation techniques
  • Translate business data stories into technical work breakdowns and estimates for agile sprints
  • Develop and maintain scalable streaming and batch data pipelines
  • Build API integrations supporting increased data volume and complexity
  • Prepare and cleanse data for downstream reporting using visualization or AI/ML tools
  • Execute projects and large tasks within timelines and develop project plans with some supervision
  • Perform other duties as assigned

Requirements

What you’ll need
  • Intermediate insurance domain knowledge
  • Intermediate Property & Casualty Insurance knowledge
  • AWS or similar platform experience: 4–6 years
  • DBT experience: 4–6 years
  • Snowflake experience: 4–6 years
  • Airflow or related experience: 4–6 years
  • Data Analysis & Profiling experience: 4–6 years
  • Data Architecture & Modelling experience: 4–6 years
  • SQL and Python experience: 4–6 years

Benefits

Comp & perks
  • Competitive salary and performance-based bonuses
  • Comprehensive benefits package
  • Career development and training opportunities
  • Flexible work arrangements (remote and/or office-based)
  • Dynamic and inclusive work culture within a globally renowned group
  • Private Health Insurance
  • Pension Plan
  • Paid Time Off
  • Training & Development