Data Engineer
Posted Updated
Summary
Design and operate production-grade ETL/ELT data pipelines, integrating data from APIs, databases, SaaS, streams, and cloud services across on-premise, AWS, and Azure environments. Focus on data modeling, quality, governance, and monitoring, applying software engineering practices like Git, CI/CD, and Infrastructure as Code.
Responsibilities:
Design and operate production-grade ETL/ELT data pipelines for data ingestion, transformation and loading.
Integrate data from APIs, databases, enterprise systems, SaaS, files, streams and cloud services.
Develop batch, incremental, CDC and event-driven data pipelines.
Design data models, schemas, data lakes and analytical datasets.
Implement data quality, validation, monitoring, reconciliation and reliability controls.
Build trusted datasets for analytics, reporting, operational visibility and AI/ML use cases.
Design secure data integration across on-premise, AWS, Azure and hybrid environments.
Ensure appropriate data security, access control, governance, lineage and auditability.
Monitor production pipelines, troubleshoot incidents and improve performance, reliability and cost.
Apply software engineering practices including Git, automated testing, CI/CD and Infrastructure as Code.
Requirments: Minimum 3-5 years of experience in data engineering, cloud data engineering, analytics engineering, software engineering, or a related discipline
At least 2 years of hands-on experience designing, building, and operating production-grade data pipelines
Demonstrated experience with data extraction, ingestion, ETL/ELT, transformation, data modelling, and data quality
Experience using AWS and/or Azure native data capabilities
Experience integrating data from APIs, databases, enterprise systems, files, or streaming sources
Experience implementing batch, incremental, CDC, and/or event-driven data pipelines
Experience working with on-premises and/or cloud environments, with an understanding of hybrid integration patterns
Experience applying software-engineering practices such as version control, automated testing, CI/CD, monitoring, and Infrastructure as Code to data solutions
Requirments: Minimum 3-5 years of experience in data engineering, cloud data engineering, analytics engineering, software engineering, or a related discipline
At least 2 years of hands-on experience designing, building, and operating production-grade data pipelines
Demonstrated experience with data extraction, ingestion, ETL/ELT, transformation, data modelling, and data quality
Experience using AWS and/or Azure native data capabilities
Experience integrating data from APIs, databases, enterprise systems, files, or streaming sources
Experience implementing batch, incremental, CDC, and/or event-driven data pipelines
Experience working with on-premises and/or cloud environments, with an understanding of hybrid integration patterns
Experience applying software-engineering practices such as version control, automated testing, CI/CD, monitoring, and Infrastructure as Code to data solutions