Job scopes:

The Senior Data Engineer will lead the enterprise-wide data transformations projects. The person will involve in developing and automating data processing pipelines for financial and Investment data modelling, analysis, and reporting from various data sources systems; The primary responsibility of this position is to establish the enterprise data Lake architecture under Microsoft Azure Data Factory, Databricks and Synapse and lead a team to deliver data driven solutions.

The primary responsibilities:

·        Lead architecture design, develop, document, and implement end-to-end data pipelines and data-driven solutions.

·        Define roadmap to transform data architecture focusing on scalability, performance, and stability for the entire data lifecycle;

·        Build data flow for data acquisition, aggregation, and modelling, using both batch and streaming paradigms.

·        Perform data analysis, data profiling, data cleansing, data lineage, data mapping and data transformation.

·        Development of high-quality code for the core data stack including data integration hub, data warehouse and data pipelines under Azure service.

·        Recommend, execute and deliver best practices in data management and data lifecycle processes, including modular development of data processes, coding and configuration standards, error handling and notification standards, auditing standards, and data archival standards.

·        Implementing security and standards, documenting technical specifications and operating procedures.

·        Collaborate across developers as part of a SCRUM team, ensuring collective team productivity

·        Provide technical support for any data issues with recommendations and resolutions.

TECHNICAL SKILLS AND EXPERIENCE REQUIREMENTS

·        3-5 years professional experience as a data engineer, software engineer, data analyst, data scientist, or related role.

·        Experience with Microsoft Azure Data Integration Stack (Azure Data Lake Gen2, Azure Data Factory, Delta Lake, SSIS, SQL Server, Azure Data Warehouse), Databricks, Spark.

·        Working experience in Investment or Real Estate industry, preferably with business and functional knowledge.

·        Expertise building ETL and data pipelines on Databricks using data engineering languages Python and SQL on Azure.

·        Knowledge and experience working with Python & SQL;

·        Proven experience with all aspects of the Data Pipeline (Data Sourcing, Transformations, Data Quality, Etc…).

·        Experience with visual modelling tools including UML

·        Proficient in using data visualization tool such as Power BI, Workiva and in standard office tools such as Excel.

·        Familiar with DevOps and Agile methodology.