▍Technical capabilities
－Enterprise Architecture: Design end-to-end data architectures to fit with overarching enterprise architecture. Define data taxonomies and data dictionaries. Curate strategic datasets, and optimize the design of data integrations, processing, and storage for data consumption patterns. Apply data correlation, denormalization, tagging, and validations at strategic points across data pipelines being executed across a common data platform.
－Solution Design: design fit-for-purpose solutions by objectively weighing considerations from resource skillsets, time pressures, costs, and operational complexity. Build simple yet scalable and extensible solutions with low operational upkeep. Solution design experience across big data, application development, automation, and infrastructure
－Customer Centricity: Engage internal customers and stakeholders to develop initial requests and ideas into real-world solutions and implementations. Focused on ascertaining the true underlying need and problem parameters. Iterate through solution options and communicate trade-offs in business and end-user terms such as experience, quality, resiliency, timelines, and cost. Develop quick proofs as an effective tool to demonstrate solution concepts and feasibility.
▍Knowledge and Experiences
－Experience in building and maintaining reliable and scalable ETL on big data platforms as well as experience working with varied forms of data infrastructure inclusive of AWS S3, Apache Hive on S3 or Databricks on S3.
－Experience working with cloud big data platforms such as AWS and relevant services such as Glue, Lake Formation, Lambda, Sagemaker, EMR, etc.
－Experience with Data Lake / Data Lakehouse Infrastructure, such as Delta Lake, Databricks, Snowflake, etc.
－Experience and deep knowledge of data modelling techniques, and relational and nonrelational databases, such as MySQL, MongoDB, etc.
－Expert knowledge of SQL, Python and Spark, Strong programming background for data exploration/analysis, and solution prototyping capabilities.
－Experience of using Data ETL solutions, such as Fivetran, Stitch, etc.
－Expertise in data modelling principles/methods including conceptual, logical & physical Data Models.
－Experience with code version control is requried, such as Gitlab, Github, Bitbucket, etc.
－Background with any of these are highly desired.
－Machine Learning, Mathematics, Statistics, Algorithm Design
－Finance or Trading Industry
－Backend Development / Restful API
▍Non-Technical capabilities
－Ownership and Leadership, and needs to mentoring Junior as Team Lead or Senior Professional
－Exceptional written, verbal, and interpersonal communication skills to be able to bridge the gap between business and technical teams.
－Ability to work within complex and challenging data environments o Proven experience in collaborating with internal, analytics, reporting and data teams.
－Ability to work independently and multi-task to meet critical deadlines in a rapidly changing environment.
－Agile Project Management Skill is highly desired.
