Bigdata Solutions Architect

Description

Deep expertise in Big Data, data warehouse, data analytics projects, and/or any Information Management related projects
Prior experience building large scale enterprise data architectures using commercial and/or open source Data Analytics technologies
Facilitate the establishment and execution of the roadmap and vision for information delivery and management; including the enterprise data warehouse, big data, BI & analytics, content management and data management
Lead a team of business analysts, data architects and data engineers to architect and deliver the solutions that fulfill the Business information needs and align with the information vision and strategy
Apply business strategy while driving technology strategy, balancing short term and long term needs to ensure that the architecture can scale and evolve accordingly
Engage an end-to-end approach by connecting all the pieces of data and deliver a streamlined model
Strong knowledge of data manipulation languages such as Spark, Scala, Impala, Hive SQL, Apache Nifi and Kafka necessary to build and maintain complex queries, streaming and real-time data pipelines
Ability to produce client ready solution architecture, business understandable presentations and good communication skills to lead and run workshops

Responsibilities

• Minimum 15 years of progressive information management solutions and end-to-end development life-cycle support and SDLC processes
• Minimum eight years leading a team including business analysts, architects, engineers, quality assurance, and operations professionals
• Bachelor's degree in computer science or relevant field from an accredited college or university; Master's degree from an accredited college or university preferred.
• Established experience delivering information management solutions to large numbers of end users
• Experience in Financial Services domain, specifically in FX Trading is strongly preferred
• Demonstrated understanding of enterprise data warehouse, big data, BI & analytics, content management and data management.
• Data modelling and architecting skills including strong foundation in data warehousing concepts, data normalization, and dimensional data modelling such as OLAP, or data vault
• Good fundamentals around security integration including Kerberos authentication, SAML and data security and privacy such as data masking and tokenization techniques
• Good knowledge in DevOps engineering using Continuous Integration/ Delivery tools
• An in depth understanding of Cloud solutions (AWS, Azure and/or Google Cloud Platform) and experienced in integrating into traditional hosting/delivery models
• Experience with two or more of the following areas including Oracle 11g, Oracle Exadata, traditional data marts, Hadoop, Databricks, Snowflake, Data Stage, ETL, Tableau, Qlikview, AI/ML techniques, Java, Impala, Hive etc.