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Birdie HR

Data Engineer

Birdie HR

Data Engineer building reliable AWS data platforms, warehouses, and ETL pipelines. Modernising legacy SQL Server infrastructure and supporting real-time Kafka data processing.

Posted 9/7/2026full-timeRemote • 🇺🇸 United StatesJuniorMid-LevelWebsite

Core Competencies

Role fit
Core Competencies

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

Demonstrates expertise in designing and maintaining scalable data pipelines and ETL/ELT processes, with a strong focus on AWS infrastructure and data quality. Proficient in SQL and Python, with hands-on experience in data warehousing and real-time data integration.

Highest-signal resume keywords
Data EngineeringSQLPythonAWSApache Airflow

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data Pipeline DevelopmentETL/ELT ProcessesData WarehousingData ModellingAPI DevelopmentData IntegrationData Quality MonitoringRelational DatabasesNon-Relational DatabasesAutomation of Data Processes
Soft Skills
Good Communication Skills
Tools & Technologies
AWS S3AWS RedshiftAWS GlueAWS LambdaKafkaGitCI/CDGitLab

Tech Stack

Tools & technologies
AirflowAmazon RedshiftApacheAWSETLKafkaPythonSQL

About the role

Key responsibilities & impact
  • Design, develop and maintain scalable and reliable data pipelines and ETL/ELT processes
  • Develop and optimise data warehouse solutions
  • Develop and maintain data infrastructure, primarily on AWS, while also supporting parts of the legacy infrastructure
  • Develop APIs and data integrations
  • Contribute to the development and maintenance of real-time data pipelines using Kafka
  • Automate and optimise data processes and workflows
  • Monitor, troubleshoot and improve the reliability, performance, security and data quality of pipelines and infrastructure
  • Work closely with the analytics team and other stakeholders to understand data needs and deliver effective solutions
  • Maintain clear and up-to-date documentation for data pipelines, infrastructure and workflows
  • Contribute to the improvement and modernisation of existing data processes and architecture

Requirements

What you’ll need
  • 2+ years of professional experience in data engineering
  • Strong SQL and Python skills
  • Hands-on experience with AWS, including S3, Redshift, Glue and Lambda
  • Hands-on experience with Apache Airflow
  • Strong understanding of data warehousing concepts and data modelling
  • Hands-on experience designing, developing and maintaining production data pipelines, with a focus on reliability, monitoring and data quality
  • Solid understanding of relational and non-relational databases
  • Familiarity with Git and CI/CD practices, preferably GitLab
  • Experience developing APIs and data integrations
  • Good written and verbal communication skills
  • Upper-intermediate English or higher

Benefits

Comp & perks
  • Remote work
  • Full-time employment