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Capgemini

Tech Lead – Data

Capgemini

. Provide technical leadership to the Data Engineering team, supporting architecture, development, and solution evolution decisions .

Posted 10/27/2026full-timeSão José dos Campos • BrazilSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing scalable data architectures in AWS, utilizing Python, SQL, and PySpark for end-to-end data pipeline development. Proficient in data governance practices and CI/CD methodologies, ensuring high-quality data solutions and technical leadership within a collaborative environment.

Highest-signal resume keywords
Technical LeadershipAWS Data ArchitecturePython DevelopmentData Pipeline DevelopmentData Governance

ATS Keywords

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Hard Skills
PythonSQLPySparkData Pipeline DevelopmentData ArchitectureData LakeData WarehouseData LakehouseREST API DevelopmentData Modeling
Soft Skills
Technical LeadershipCollaborationProblem-SolvingCommunicationAgile Methodologies
Tools & Technologies
AWS GlueAWS RedshiftAWS S3AWS Step FunctionsAWS LambdaJenkinsDockerGitBitbucketJira
Industry Keywords
Data EngineeringMedallion ArchitectureData GovernanceData QualityData LineageETLELTAgileScrumKanban

Tech Stack

Tools & technologies
Amazon RedshiftApacheAWSDockerETLJenkinsPySparkPythonSQL

About the role

Key responsibilities & impact
  • Provide technical leadership to the Data Engineering team, supporting architecture, development, and solution evolution decisions
  • Define and implement scalable, resilient data architectures in AWS environments
  • Design, develop, and evolve end-to-end data pipelines, covering data ingestion, transformation, processing, and serving
  • Contribute directly to development using Python, SQL, and PySpark to process large volumes of data
  • Design Data Lake, Data Warehouse, and Data Lakehouse solutions, applying best practices for data modeling and organization
  • Implement and evolve architectures based on the Medallion Architecture, including Bronze, Silver, and Gold layers
  • Work with AWS services, primarily Glue, Redshift, S3, Step Functions, and Lambda
  • Develop and integrate REST APIs for communication between systems, applications, and different data sources
  • Define technical standards and best practices for pipeline development, version control, testing, documentation, and maintenance
  • Ensure data governance, quality, traceability, and data lineage across data solutions
  • Implement and promote automated testing, including end-to-end pipeline testing
  • Support CI/CD practices for Data Engineering using Jenkins, Docker, Git, and Bitbucket
  • Conduct technical reviews and support the team in resolving complex issues
  • Translate business needs into robust technical solutions, assessing impacts, dependencies, and architectural alternatives
  • Document architectures, technical decisions, and solutions using Confluence
  • Work in an agile environment, tracking demands and deliverables through Jira and Scrum/Kanban methodologies

Requirements

What you’ll need
  • Strong experience as a Tech Lead, Technical Lead, or Senior Data Engineer with technical leadership and direction responsibilities
  • Advanced experience with Python and SQL for manipulating, transforming, and processing large volumes of data
  • Strong experience building end-to-end data pipelines, including data ingestion, transformation, and serving processes (ETL/ELT)
  • Experience with Data Architecture and Data Engineering in AWS environments
  • Practical knowledge of key AWS data services, such as Glue, Redshift, S3, Step Functions, and Lambda
  • Experience with distributed processing using PySpark
  • Experience with Data Lake, Data Warehouse, and Data Lakehouse architectures
  • Knowledge of the Medallion Architecture, including Bronze, Silver, and Gold layers
  • Experience with data modeling in analytical environments and using formats such as Parquet and CSV
  • Knowledge of transactional table technologies, such as Delta Lake and/or Apache Iceberg
  • Experience consuming and developing REST APIs for integration between systems and data sources
  • Knowledge of data governance practices, including Data Lineage, Data Quality, and pipeline traceability
  • Knowledge of CI/CD practices applied to Data Engineering, using tools such as Jenkins and Docker
  • Experience with code version control and collaboration using Git and Bitbucket
  • Experience with Jira, Confluence, and agile methodologies such as Scrum and Kanban
  • Fluent English – mandatory, with the ability to participate in meetings, technical discussions, and professional interactions in English with different stakeholders and global teams

Benefits

Comp & perks
  • Structured career development plan and personalized learning paths
  • Corporate University, with access to Harvard and Pluralsight
  • Official certifications with partners such as SAP, AWS, Microsoft, and Salesforce
  • Language courses through EF Education First (English, Spanish, French, and German)
  • Medical and dental insurance
  • TotalPass and Equilibrium (physical and mental well-being)
  • Private pension plan and life insurance
  • Family Care Program: extended maternity and paternity leave, fertility support, and personalized health and well-being guidance
  • Meal voucher
  • Home office allowance
  • Benefits club
  • Flexible work models, which may include remote, hybrid, or on-site work, depending on project needs