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Interval Group

Lead Data Platform Architect – AWS

Interval Group

. Define and implement AWS Data Lake, Lakehouse, and Data Warehouse architectures .

Posted 11/11/2026contractRemote • IrelandSeniorWebsite

Core Competencies

Role fit
Core Competencies

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

Demonstrates expertise in designing and implementing AWS Data Lake, Lakehouse, and Data Warehouse architectures, with a strong focus on data governance, IAM, and GDPR compliance. Proven ability to lead technical teams, mentor Data Engineers, and develop robust data integration solutions using modern technologies.

Highest-signal resume keywords
AWS Data Lake ArchitectureData Governance ImplementationTechnical LeadershipSpark and Kafka ExperienceTerraform and CI/CD Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
AWS GlueAWS AthenaAWS RedshiftAWS EMRAWS KinesisSparkKafkaDataOpsSemantic Data ModelingData Architecture
Soft Skills
Technical LeadershipMentoringCode ReviewExcellent English Skills
Tools & Technologies
AirflowStep FunctionsDbtTerraformCI/CD
Certifications & Qualifications
AWS Certification
Industry Keywords
Data LakehouseData WarehouseData IntegrationGDPR ComplianceIAMKMS

Tech Stack

Tools & technologies
AirflowAmazon RedshiftAWSKafkaSparkTerraform

About the role

Key responsibilities & impact
  • Define and implement AWS Data Lake, Lakehouse, and Data Warehouse architectures
  • Make technical architecture decisions and contribute to hands-on development using AWS Glue, Athena, Redshift, EMR, and Kinesis
  • Develop batch and streaming architectures with Spark, Kafka, and Iceberg or Delta Lake
  • Build ontologies, semantic layers, and data integration concepts
  • Orchestrate workflows with Airflow/MWAA, Step Functions, and dbt
  • Implement data governance, IAM, KMS, and GDPR requirements
  • Develop infrastructure and proof-of-concept solutions using Terraform, CI/CD, and DataOps
  • Provide technical leadership, conduct code reviews, and mentor Data Engineers

Requirements

What you’ll need
  • Several years of experience designing and implementing AWS data platforms
  • Strong practical knowledge of AWS Analytics Services and Lakehouse architectures
  • Hands-on experience with data pipelines, integrations, and proof-of-concept solutions
  • Experience with Spark, Kafka, and modern data processing technologies
  • Knowledge of semantic data modeling and data architecture
  • Knowledge of Terraform, CI/CD, and DataOps
  • Experience in technical leadership and engineering delivery
  • Excellent English skills
  • AWS certification is desirable
  • German language skills are desirable

Benefits

Comp & perks
  • Flexible working hours
  • Freedom to choose projects independently
  • Access to exciting projects across various industries through the platform
  • Support from a dedicated team for any questions
  • Independent working environment
  • Access to a strong professional network
  • Opportunities for professional development