FT
FCamara Consulting & TrainingData Engineer – AWS Stack
Data Engineer building solutions on AWS for high - performance data processing. Leading initiatives in data architecture and analytics for operational support.
About the role
- Design, build, and optimize scalable ETL and Structured Streaming pipelines in Azure Databricks for real-time and batch ingestion of Flight Status data
- Design and implement data ingestion and processing pipelines that consolidate heterogeneous data sources, including APIs, event streams, and file-based feeds, into the OAG lakehouse (Azure Databricks + Delta Lake), ensuring data consistency, reliability, and scalability
- Implement and monitor data quality using automated validation, alerting, and observability practices
- Develop and maintain orchestration workflows in Apache Airflow, coordinating ingestion and transformation processes across multiple data flows
- Build reusable frameworks for schema evolution, error handling, deduplication, and auditing
- Collaborate with data platform, analytics, and product teams to define SLAs, data contracts, and performance targets
- Optimize Spark and Delta Lake performance for scalability, latency, and cost efficiency
- Implement CI/CD pipelines and automation for data workflows using Azure DevOps or equivalent tools
- Mentor engineers, review code, contribute to platform design discussions and planning, and help grow data engineering competencies in the team and across OAG
Requirements
- Proven track record in data engineering with a strong focus on ETL development and streaming data architectures
- Experience with Azure Databricks, Apache Spark (Structured Streaming), and Delta Lake
- Proficiency in Python (PySpark) and SQL, with experience transforming large-scale, complex datasets
- Hands-on experience in data orchestration and workflow automation (e.g., Apache Airflow or similar)
- Experience working in a cloud data environment (preferably Azure) across storage, compute, and pipeline services
- Familiarity with streaming or messaging technologies (e.g., Kafka, Event Hubs)
- Strong understanding of data quality, validation, and observability practices
- Ability to deliver production-grade solutions with a results-oriented and ownership-driven mindset
- Experience implementing CI/CD and version-control practices using Azure DevOps, GitHub Actions, or similar tools
- Excellent analytical, communication, and collaboration skills
- Strong understanding of modern data engineering patterns and ability to design scalable, modular, and reliable data systems
Benefits
- Company-provided free lunch every day
- Private health insurance
- Company bonus scheme
- Voluntary participation in a company-supported retirement scheme
- Generous annual leave policy that grows with each year of service
- Day off during your birthday month
- Participation in team-building activities
- Participation in team workshops
- Participation in group learning sessions
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