Mid/Sen Data Engineer

Key Responsibilities:

Stay current with emerging technologies and best practices in data engineering, big data processing, and cloud computing to drive continuous improvement and innovation.
Collaborate with data scientists and analysts to understand data requirements, perform data wrangling and preprocessing, and support machine learning model development and deployment.
Build and maintain data integration workflows using tools and technologies such as Apache Spark, Apache Airflow, Kafka, and AWS Glue.
Design, develop, and optimize scalable data pipelines and ETL processes to ingest, transform, and load large volumes of structured and unstructured data from various sources into our data warehouse.
Implement data models, schemas, and architectures to support business analytics, reporting, and data visualization requirements.

Objectives:

Data Infrastructure Excellence. Design, build, and manage a cutting- edge data infrastructure that ensures scalability, reliability, and security to meet current and future business demands.
Collaboration, Innovation, and Continuous Improvement. Foster a culture of innovation and continuous improvement in data practices, collaborating closely with key stakeholders to leverage data in driving business solutions and shaping the company’s data and analytics strategy.
Data Integration and Insight Generation. Develop and maintain state- of- the- art ETL processes and analytics models that integrate data from diverse sources, ensuring high data accuracy and timeliness, and providing actionable insights for strategic decision- making.

Qualifications:

Data Security, Data Quality Assurance and Testing
Proficient in data engineering technologies and languages (e.g., SQL, Python, Java, Scala) and experience with cloud data services (e.g., AWS, GCP, Azure).
Expertise in data visualization and business intelligence tools (e.g., Tableau, Power BI).
Advanced skills in data modeling, ETL development, and data integration and pipeline construction.
Performance tuning and Optimization
Having a Bachelor&039;s in Computer Science, Data Science, Engineering, or a related field.
Solid understanding of machine learning algorithms and statistical analysis.
Strong experience in Big Data technologies like Hadoop. Spark
02+ years of practical experience in designing and managing data warehouses, lakes, and real- time data processing systems.
Excellent communication and collaboration skills, with the ability to translate complex data insights into actionable business strategies.

What We Offer:

The opportunity to work on exciting projects at the forefront of the personalization and print- on- demand industry.
The opportunity to work on innovative RnD initiatives with R2Studio Research Lab on AI- enabled large- scale products recommendation and discovery.
A dynamic, creative, and supportive work environment where your contributions are highly valued.
Competitive compensation package, including benefits and performance- based incentives.
Professional development opportunities to grow your skills and career.

Cập nhật gần nhất lúc: 2024-07-03 09:20:05