Data Engineer designing and implementing big data solutions at DATAIS. Collaborating with clients to deliver actionable business insights and innovative data products in a hybrid environment.
About the role
- Senior Data Engineer at Razer leading initiatives in data engineering and AI infrastructure. Collaborating across teams to develop robust data solutions and enhancing AI/ML projects.
Responsibilities
- Lead the design and development of robust, scalable data pipelines for both traditional analytics and AI/ML workloads
- Build and maintain data architectures including data warehouses, data lakes, and real-time streaming solutions using tools like Redshift, Spark, Flink, and Kafka
- Implement and optimize data orchestration workflows using Airflow and data transformation processes using DBT
- Design and implement dimensional modeling solutions, leading dimensional modeling design initiatives
- Develop automated data workflows and integrate with DevOps/MLOps frameworks using Docker, Kubernetes, and cloud infrastructure
- Implement best practices for data governance, including data quality, security, compliance, data lineage, and access control
- Collaborate with data scientists, analysts, and business stakeholders to understand technical requirements and deliver reliable data infrastructure
- Demonstrate strong business sensitivity to ensure data solutions align with business objectives and requirements
- Support AI/ML initiatives by building feature stores, vector databases, and real-time inference pipelines
- Continuously explore and adopt new technologies in data engineering and AI/ML space
- Proactively drive new initiatives and mentor junior team members
Requirements
- Bachelor's degree in Computer Science, Data Engineering, Statistics, or related field
- 5+ years of experience in data engineering with focus on scalable data architectures
- Expert proficiency in Python and SQL programming languages
- Hands-on experience with AWS Redshift, Apache Airflow, and DBT (Data Build Tool)
- Strong experience with big data frameworks: Apache Spark, Apache Flink, and Apache Kafka
- Solid understanding of Linux, Docker, and Kubernetes for containerization and orchestration
- At least one cloud platform experience (AWS preferred, but GCP or Azure acceptable)
- Proven experience in dimensional modeling design and implementation
- Strong business acumen with sensitivity to business requirements and ability to translate them into robust technical data solutions
- Fluent in English (reading, writing, and verbal communication)
- Experience in data governance including data quality, security, access management, and data lineage
- Foundational knowledge of AI/ML workflows, model deployment pipelines, and LLM integration patterns
- Demonstrated ability to lead technical initiatives and drive adoption of new technologies independently
- Strong analytical and communication skills with experience working across cross-functional teams
Benefits
- Health insurance
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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