Role Summary
WAISL Digital is looking for a Data Engineer to build and maintain scalable data pipelines and data platforms that support its AI Center of Excellence. The role focuses on reliable data processing, data quality, cloud data services, data modeling, and providing clean and accessible data for data science and machine learning initiatives.
Key Responsibilities
- Data Platforms: Design, build, deploy, and maintain large-scale data processing systems, data lakes, and data warehouses.
- ETL/ELT Pipelines: Develop scalable and reliable pipelines to ingest and process data from diverse sources.
- Data Quality: Maintain high-quality data and implement data governance and security standards across data platforms.
- Data Collaboration: Work with Data Scientists to understand data requirements and provide reliable datasets for modeling and machine learning.
- Performance Optimization: Optimize data systems for performance, scalability, reliability, and cost efficiency.
- Data Architecture: Collaborate on data modeling and schema design to support scalable data solutions.
Key Qualifications
- Education: Bachelor's or Master's degree in Computer Science or a related field.
- Experience: 3+ years of professional experience in a Data Engineer role.
- Core Technical Skills: Expert-level SQL skills and strong programming experience in Python, Scala, or Java.
- Big Data: Experience with big data technologies such as Spark, Hadoop, or Kafka.
- Cloud Data: Experience with cloud data services such as AWS Redshift/S3, Azure Synapse/Data Lake, or GCP BigQuery.
- Data Engineering Concepts: Strong knowledge of data modeling and data warehousing concepts.
- Additional Skills: Understanding of data quality, governance, security, and scalable data processing systems.
About WAISL Digital
WAISL Digital is focused on transforming airport ecosystems through digital technologies and solutions. The organization works on technology initiatives supporting the future of aviation, including data and AI-driven capabilities.