An ideal candidate should have experience as below -
Leading via influence and assist in establishing a world class Data Engineering practice by reimagining all existing processes, tools and skill sets
Identify and advocate use-cases for the Fund’s newly established data platform; assist in planning and migration of Data and applicable services onto the Fund’s Data Solutions
Assist projects with Data Engineering associated scope, planning, resourcing, scheduling, and costing
Represent the Technology Data and Analytics team in Fund wide data initiatives and the roll-out of Fund wide data capabilities
Develop and implement databases, data collection systems, data analytics and other techniques that optimise statistical efficiency and quality
Acquire data from primary or secondary data sources and maintain databases/data systems
Identify, analyze, and interpret trends or patterns in complex data sets
Provide governance over vendor outcomes and associated deliverables
Lead and motivate the team to ensure delivery of exceptional Data Engineering quality outcomes whilst creating a sense of urgency around genuinely delivering better experiences for our members and colleagues
Liaise effectively with project team members, business stakeholders and external vendors to build strong partnerships to help create a collaborative, transparent, and high performing culture with a strong delivery mind set.
Skills & Experience:
Experience working in complex enterprise Data Environments
Proven advanced Engineering experience in Python, Spark, SQL and related languages.
10+ years’ experience in designing and building advanced Data Pipelines and Data Warehouses at an enterprise scale.
Proven DevOps experience inclusive of creating CI/CD/CT pipelines for data engineering and analytics using Azure Devops.
Strong experience in one or more of the following public Data cloud platforms, Azure Synapse, AWS Redshift, Google Cloud, with preference for Azure Cloud Synapse and ADF, ADB