Octus is seeking a Data Engineer to design, develop, and lead scalable data ingestion and transformation pipelines.

Requirements

Lead the design and development of data ingestion and transformation pipelines, ensuring scalability, efficiency, and reliability across diverse data sources (APIs, web data, internal feeds, etc.).
Serve as a key contributor and mentor within the data engineering team, guiding architecture, design, and implementation decisions.
Architect and manage data pipelines and orchestration workflows using AWS services such as MWAA (Airflow), Lambda, ECS, and SQS.
Implement and maintain infrastructure as code (IaC) using Terraform, ensuring reproducibility and compliance with cloud standards.
Partner with data analysts, scientists, and backend engineers to ensure data consistency, discoverability, and reliability.
Apply best practices in data modeling, schema design, and ETL/ELT processes for high-volume structured and semi-structured data.
Ensure data quality and lineage through automated testing, monitoring, and alerting.
Promote continuous improvement through code reviews, observability practices, and team-wide knowledge sharing.
Collaborate closely with technology leadership to align data platform development with business strategy and product goals.
Stay up to date with industry trends in data engineering, cloud architecture, AI/ML integration, and automation.

Benefits

Octus is seeking a Data Engineer to design, develop, and lead scalable data ingestion and transformation pipelines.

Lead the design and development of data ingestion and transformation pipelines, ensuring scalability, efficiency, and reliability across diverse data sources (APIs, web data, internal feeds, etc.).
Serve as a key contributor and mentor within the data engineering team, guiding architecture, design, and implementation decisions.
Architect and manage data pipelines and orchestration workflows using AWS services such as MWAA (Airflow), Lambda, ECS, and SQS.
Implement and maintain infrastructure as code (IaC) using Terraform, ensuring reproducibility and compliance with cloud standards.
Partner with data analysts, scientists, and backend engineers to ensure data consistency, discoverability, and reliability.
Apply best practices in data modeling, schema design, and ETL/ELT processes for high-volume structured and semi-structured data.
Ensure data quality and lineage through automated testing, monitoring, and alerting.
Promote continuous improvement through code reviews, observability practices, and team-wide knowledge sharing.
Collaborate closely with technology leadership to align data platform development with business strategy and product goals.
Stay up to date with industry trends in data engineering, cloud architecture, AI/ML integration, and automation.