Roles & Responsibilities
We're looking for a seasoned Big Data Engineering Lead with expertise in Scala, Python, and PySpark to lead our client data engineering team. You'll be responsible for designing and implementing scalable, efficient, and fault-tolerant data pipelines, as well as mentoring team members and driving technical innovation.
Key Responsibilities :
- Design and develop large-scale data pipelines using Scala, Python, and PySpark
- Lead and mentor a team of data engineers to build and maintain data architectures
- Collaborate with cross-functional teams to identify data requirements and implement data-driven solutions
- Ensure data quality, integrity, and security across all data pipelines
- Develop and maintain technical documentation for data pipelines and architectures
- Stay up-to-date with industry trends and emerging technologies in big data, cloud computing, and data engineering
- Drive technical innovation and recommend new tools and technologies to improve data engineering capabilities
Requirements :
5+ years of experience in big data engineering, with expertise in Scala, Python, and PySparkStrong experience with big data technologies such as Apache Spark, Hadoop, and KafkaExperience with cloud-based data platforms such as AWS, GCP, or AzureStrong understanding of data architecture, data governance, and data securityExcellent leadership and mentoring skills, with experience leading high-performing teamsStrong communication and collaboration skills, with ability to work with cross-functional teamsBachelor's or Master's degree in Computer Science, Engineering, or related fieldTell employers what skills you have
Mentoring
Technical Documentation
PySpark
Apache Spark
Scala
Azure
Big Data
Cloud Computing
Pipelines
Hadoop
Data Quality
Data Governance
Data Engineering
Python
Data Architecture
GCP