we are looking for a Data Engineer.
What youll do:
Design, build, and optimize large-scale data pipelines and workflows for both batch and real-time processing.
Architect and maintain Airflow-based orchestration frameworks to manage complex data dependencies and data movement.
Develop high-quality, maintainable data transformation and integration processes across diverse data sources and domains.
Lead the design and implementation of scalable, cloud-based data infrastructure ensuring reliability, performance, and cost efficiency.
Drive data modeling and data architecture practices to ensure consistency, reusability, and quality across systems.
Collaborate closely with Product, R&D, BizDev, and Data Science teams to define data requirements, integrations, and delivery models.
Own the technical roadmap for key data initiatives, from design to production deployment.
What youll do:
Design, build, and optimize large-scale data pipelines and workflows for both batch and real-time processing.
Architect and maintain Airflow-based orchestration frameworks to manage complex data dependencies and data movement.
Develop high-quality, maintainable data transformation and integration processes across diverse data sources and domains.
Lead the design and implementation of scalable, cloud-based data infrastructure ensuring reliability, performance, and cost efficiency.
Drive data modeling and data architecture practices to ensure consistency, reusability, and quality across systems.
Collaborate closely with Product, R&D, BizDev, and Data Science teams to define data requirements, integrations, and delivery models.
Own the technical roadmap for key data initiatives, from design to production deployment.
Requirements:
6+ years of experience as a Data Engineer working on large-scale, production-grade systems.
Proven experience architecting and implementing data pipelines and workflows in Airflow – must be hands-on and design-level proficient.
Strong experience with real-time or streaming data processing (Kafka, Event Hubs, Kinesis, or similar).
Advanced proficiency in Python for data processing and automation.
Strong SQL skills and deep understanding of data modeling, ETL/ELT frameworks, and DWH methodologies.
Experience with cloud-based data ecosystems (Azure, AWS, or GCP) and related services (e.g., Snowflake, BigQuery, Redshift).
Experience with Docker, Kubernetes, and modern CI/CD practices.
Excellent communication and collaboration skills with experience working across multiple stakeholders and business units.
A proactive, ownership-driven approach with the ability to lead complex projects end-to-end.
6+ years of experience as a Data Engineer working on large-scale, production-grade systems.
Proven experience architecting and implementing data pipelines and workflows in Airflow – must be hands-on and design-level proficient.
Strong experience with real-time or streaming data processing (Kafka, Event Hubs, Kinesis, or similar).
Advanced proficiency in Python for data processing and automation.
Strong SQL skills and deep understanding of data modeling, ETL/ELT frameworks, and DWH methodologies.
Experience with cloud-based data ecosystems (Azure, AWS, or GCP) and related services (e.g., Snowflake, BigQuery, Redshift).
Experience with Docker, Kubernetes, and modern CI/CD practices.
Excellent communication and collaboration skills with experience working across multiple stakeholders and business units.
A proactive, ownership-driven approach with the ability to lead complex projects end-to-end.
This position is open to all candidates.
