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
