Place client value and human experience at first priorities.
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/MLTeam
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
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
Educate, enable, and coach teams on Data Machine Learning Engineers 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
Bachelor\xe2\x80\x99s Degree/Masters Degree in Computer Science/Data Analytics or similar technology field
Minimum 7 years of designing, building and operationalizing large scale enterprise data solutions and applications (both with batch and streaming data)
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 Stream platforms and real-time aggregation platforms like Kafka, Kinesis, Spark, Flink, KSQL 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
Good exposure to concepts like Serverless computing, CI/CD, Containerization, Infrastructure as Code, code version control and automated testing
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
Kindly understand that only shortlisted candidates will be notified. EnviroDynamics Solutions Pte Ltd Poon Wai Soon, Bernard Reg. No: R2197713 EA License No.: 12C6285
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