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Key Responsibilities
As part of the Data Engineering practice, some of the key responsibilities include:
- Developing, testing and implementing business systems of the highest complexity
- Ensures cross team integration and proper hand-offs of code/tasks to meet schedules
- Designs reusable software components and incorporates reusable assets into the application design
- Research and evaluate Data Engineering tools and frameworks
- Participate on POCs and assist in client presentations
- Assist engineering leadership in hiring and interviewing top talent
- Mentor junior staff conduct design/code/test reviews
- Assist in developing centre of excellence, best practices, documentation, re-usable assets
- Proficient in distributed architecture, understanding of required infrastructure setup
- Mentor junior team members
Qualifications
- Minimum 15+ years of experience with significant experience in the Data Engineering space
- Experience in designing and building robust and highly scalable data platform and data pipelines
- Experience with leading a team of experienced Data Engineers
- Prior experience working in the consulting space will be highly advantageous
- Strong programming proficiency using 1 or 2 of the following languages: Scala, Python, Java
- Extensive experience with data modelling and designing/supporting both streaming and batch ETL pipelines
- Clear understanding of distributed computing, especially in databases
- Hands-on in SQL and NOSQL with a deep understanding of query optimization
- Experience with open-source technologies (Spark, Kafka, Presto, Hive, Cassandra etc.)
- Experience working on any of the Cloud platforms (GCP, AWS, Azure)
- Good to have: Certification for Data Engineers or Solution Architect in 1 or more Cloud Technologies (AWS, GCP, Azure)
- Strong communications skills and presentation skills to C levels
- Ability to manage numerous requests concurrently and be able to prioritize and deliver