Responsibilities

Purpose - Place client value and human experience at the center of everything we do - Develop and deliver value to clients by building large scale enterprise data pipelines to capture, transform and store date to support reporting, automated systems and AI/ML Team - Build a world-class team with experts in Data engineering - Create a culture of excellence and lead with confidence, charisma, context, and humility, working effectively at all levels Delivery - Lead design & delivery of Data pipelines to drive material impact and drive disruptive transformation across our clients in public and private sectors - Support development of go-to-market plans for Data engineering, understand strategic opportunities, develop trusted partnerships, and deliver social progress - Thought leadership for data engineering and scaling deployments Partnership - Educate, enable, and coach teams on Data Machine Learning Engineers in Company, clients and in the broader community - Adopt a cloud-first strategy to enhance agility and elasticity by partnering with vendors to support specific public sector needs - Harness cutting-edge research through a triple helix partnership between research, industry, and government to drive state-of-the-art with bi-directional rotations

Requirements

• 5+ years of experience in software development.
• Bachelor\xe2\x80\x99s degree/Diploma in Computer Science, Computer Studies, Information Technology, or related disciplines
• Strong stakeholder and project management skills, and ability to grow and upsell in the client environment
• Experience with Kafka, .NET, CI/CD, SQL and/or DBT
• Cloud native development experience, preferably with AWS and docker
• Sound knowledge of best practices in data engineering and data security
• Knowledge on cloud security controls, DevOps and CICD pipelines
• Experience with AWS EKS, Amazon Aurora, AWS RDS, AWS S3 and AWS CloudWatch
• Experience using one or more of AWS / Azure / GCP data and analytics services in combination with custom solutions - Spark, Azure Data Lake, Databricks, Snowflake, HDInsights, SQL DW, DocumentDB, Glue, Athena, Elastic Pool etc.
• Experience with multiple data storage solutions for analytics, operational and archival purposes like MongoDB, Cassandra, HBase, Redis, PostgreSQL, MySQL, DB2, Neo4j, S3 etc.
• Experience with data transformation tools/platforms like: dbt, Alteryx, Datameer, dataform, Informatica, Talend etc. and their data quality management features
• Mastered at least one core language: Python, Scala, Java
• Experience building historical and real-time operational \xe2\x80\x98feature layers\xe2\x80\x99 to support AI/ML teams
• Excellent understanding of the state of Data Engineering evolution in the industry through active tracks of improving knowledge and skills (e.g. courses, podcasts, books, experimentation, open source volunteering, tech meetups etc.)
• Track record of delivering scalable Data pipeline services running in production.
• Strong ability to communicate with a broad range of clients, colleagues, and partners across a variety of contexts and formats.
• Strong ability to explain design decisions and provide alternatives supported by analysis like pro/con, past experiences etc.
• Strong ability to develop and maintain relationships amongst clients, colleagues, and partners
• Demonstrated capability to lead, inspire, coach and mentor team members and colleagues.
• Ability to work within an unstructured environment with ability to multitask well