3 Data Tracing Jobs

As a Data Analyst in this role, you will be responsible for analyzing data requirements and identifying disparate data sources needed for consolidation and distribution. You will document functional specifications and collaborate with the technology team to ensure timely delivery. It will be your responsibility to review logical and conceptual data models to ensure alignment with business requirements. Your role will involve working closely with stakeholders to gather requirements and produce detailed business specifications. You will validate solution implementations to guarantee they meet both business and functional requirements. Providing production deployment support and investigating data quality issues will also be part of your responsibilities. To excel in this position, you must have subject matter expertise in the financial industry, specifically in wholesale loans/lending business, Capital Markets, Finance, or Risk Reporting. Proficiency in database management and SQL is a must. Excellent documentation and analytical skills are essential for producing process flow diagrams, business modeling, and functional designs. Your proficiency in MS Office tools such as Word, Excel, Visio, and PowerPoint, particularly in using Excel for data analysis, will be crucial for this role. Experience with data tracing and lineage efforts, as well as knowledge of logical and physical data models, will further enhance your capabilities in fulfilling the responsibilities of this position.,

As a Data Ops Capability Deployment Analyst at our organization, you will be a seasoned professional contributing to the development of new solutions, frameworks, and techniques while improving processes and workflow for the Enterprise Data function. Your role will involve integrating subject matter and industry expertise within a defined area, requiring an in-depth understanding of how different areas collectively integrate within the sub-function to contribute to the overall business objectives. Your primary responsibility will be to perform data analytics and analysis across various asset classes, as well as to establish data science and tooling capabilities within the team. You will collaborate closely with the wider Enterprise Data team, particularly the front-to-back leads, to deliver on business priorities effectively. Joining the B & I Data Capabilities team within the Enterprise Data, you will be involved in managing the Data quality/Metrics/Controls program and implementing improved data governance and data management practices throughout the region. The focus of the Data quality program will be on enhancing our approach to data risk and meeting regulatory commitments in this area. Key Responsibilities: - Utilize data engineering background and expertise in Distributed Data platforms and Cloud services. - Demonstrate a sound understanding of data architecture and integration with enterprise applications. - Research and assess new data technologies, data mesh architecture, and self-service data platforms. - Collaborate with the Enterprise Architecture Team to define and refine the overall data strategy. - Address performance bottlenecks, design batch orchestrations, and deliver Reporting capabilities. - Conduct complex data analytics on large datasets including data cleansing, transformation, joins, and aggregation. - Develop analytics dashboards and data science capabilities for Enterprise Data platforms. - Communicate findings and propose solutions to stakeholders effectively. - Translate business and functional requirements into technical design documents. - Collaborate with cross-functional teams such as Business Analysis, Product Assurance, Platforms and Infrastructure, Business Office, Control and Production Support. - Prepare handover documents and manage SIT, UAT, and Implementation processes. - Demonstrate a deep understanding of how the development function integrates within the overall business/technology to achieve objectives. - Perform other assigned duties as necessary. Skills & Qualifications: - 10+ years of active development background in Financial Services or Finance IT. - Experience with Data Quality/Data Tracing/Data Lineage/Metadata Management Tools. - Hands-on experience with ETL using PySpark on distributed platforms, data ingestion, Spark optimization, and batch orchestration. - Proficiency in Hive, HDFS, Airflow, and job scheduler. - Strong programming skills in Python with experience in data manipulation and analysis libraries (Pandas, Numpy). - Ability to write complex SQL/Stored Procs. - Experience with DevOps, Jenkins/Lightspeed, Git, CoPilot. - Proficient in one or more BI visualization tools such as Tableau, PowerBI. - Proven experience in implementing Datalake/Datawarehouse for enterprise use cases. - Exposure to analytical tools and AI/ML is desired. Education: - Bachelor's/University degree, master's degree in information systems, Business Analysis, or Computer Science. If you are looking for a challenging opportunity where you can utilize your expertise in data analytics, data engineering, and data science, this role offers a dynamic environment where you can contribute to the growth and success of the Enterprise Data function within our organization.,

Subject matter expertise in financial industry - wholesale loans/lending business OR Capital Markets OR Finance OR Risk Reporting - Experience with database and SQL is required. - Excellent documentation, analytical skills to produce process flow diagrams, business modelling and functional design. - Proficiency in MS Office (Word, Excel, Visio, PowerPoint) with extensive experience using Excel for data analysis. - Experience with Data tracing/ Lineage efforts - Knowledge of logical and physical data models - Analyze data requirements and identify disparate data sources required for consolidation and distribution - Document functional specifications and coordinate delivery of the same with technology team. - Review logical and conceptual data models in alignment with business requirements. - Work with the stakeholders to understand and gather requirements and produce business specifications - Validate solution implementations and ensure they meet business and functional requirements - Provide production deployment support and investigate data quality issues. - Work with various technology leads to ensure the gaps in the data completeness or accuracy are bridged