Required Senior Data Engineer
What your day will look like:
Design, plan, and build all aspects of the platforms data, machine learning (ML) pipelines, and infrastructure.
Build and optimize an AWS-based Data Lake using best practices in cloud architecture, data partitioning, metadata management, and security to support enterprise-scale data operations.
Collaborate with engineers, data analysts, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL/ELT patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring.
What your day will look like:
Design, plan, and build all aspects of the platforms data, machine learning (ML) pipelines, and infrastructure.
Build and optimize an AWS-based Data Lake using best practices in cloud architecture, data partitioning, metadata management, and security to support enterprise-scale data operations.
Collaborate with engineers, data analysts, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL/ELT patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring.
Requirements:
Have 5+ years of hands-on experience in designing and maintaining big data pipelines across on-premises or hybrid cloud environments, with proficiency in both SQL and NoSQL databases within a SaaS framework.
Proficient in one or more programming languages: Python, Scala, Java, or Go.
Experienced with software engineering best practices and automation, including testing, code reviews, design documentation, and CI/CD.
Experienced in building and designing ML/AI-driven production infrastructures and pipelines.
Experienced in developing data pipelines and maintaining data lakes on AWS – big advantage.
Familiar with technologies such as Kafka, Snowflake, MongoDB, Airflow, Docker, Kubernetes (K8S), and Terraform – advantage.
Bachelor's degree in Computer Science or equivalent experience.
Strong communication skills, fluent in English, both written and verbal.
A great team player with a can-do approach.
Have 5+ years of hands-on experience in designing and maintaining big data pipelines across on-premises or hybrid cloud environments, with proficiency in both SQL and NoSQL databases within a SaaS framework.
Proficient in one or more programming languages: Python, Scala, Java, or Go.
Experienced with software engineering best practices and automation, including testing, code reviews, design documentation, and CI/CD.
Experienced in building and designing ML/AI-driven production infrastructures and pipelines.
Experienced in developing data pipelines and maintaining data lakes on AWS – big advantage.
Familiar with technologies such as Kafka, Snowflake, MongoDB, Airflow, Docker, Kubernetes (K8S), and Terraform – advantage.
Bachelor's degree in Computer Science or equivalent experience.
Strong communication skills, fluent in English, both written and verbal.
A great team player with a can-do approach.
This position is open to all candidates.
