Sr. Big Data Architect

Role: Sr. BIG Data Solutions Architect

Responsibilities:

• 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

Requirement:

• 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.