Financial Crimes Compliance Engineering – Data Analyst, FCC Engineering

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This knowledge enables us to build long-lasting software solutions, and to innovate with a purpose.</span></p>\n<p><span>Compliance Engineering is looking to fill a Data Analyst role within FCC Engineering.</span></p>\n<p>&nbsp;</p>\n<p><span><b><u>How will you fulfil your potential</u></b></span></p>\n<p><span>The Financial Crimes Compliance (FCC) Engineering, under Global Compliance, is responsible for Architecture, Design, Development and Implementation of best-in-class software solutions to ensure compliance with regulatory mandates and mitigate any reputational and related risks to the firm. A key component of second line of defense for the firm, FCC Engineering builds and maintains technology solutions for Know Your Customer (KYC), Anti-Money Laundering Detection (AML Monitoring), Sanctions Screening, Anti-Bribery and Corruptions and all other related FCC areas.</span></p>\n<p><span>With constantly changing regulatory and technology landscape, FCC engineering strives to stay ahead of the curve through continuous innovation.</span></p>\n<p><span>As a Data Analyst within FCC engineering, you will be a hands-on contributor responsible for developing and supporting scalable FCC data solutions. You will work closely with architects, product partners and compliance stakeholders to implement end-to-end FCC data strategies, curate high quality single source of truth databases and support the development of ML/AI capabilities on AWS/Snowflake and related Cloud ecosystem. This role is implementation heavy and expects strong engineering ownership from design through production support.</span></p>\n<p><span>In this role, you will contribute to innovation and will be responsible for, among other related functions, the following:</span></p>\n<ul>\n <li><span>Contributes to the design, development, and maintenance of data pipelines and ETL processes for financial crimes compliance applications, ensuring data synchronization with production systems.</span></li>\n <li><span>Assist in the development and maintenance of data products for the “Single Source of Truth” financial crimes compliance data fabric, including on-prem and cloud storage and real-time/batch compute.</span></li>\n <li><span>Support the implementation of storage and compute separation with true data federation to avoid data duplication, eliminate compute resource conflict and ensure cloud-native architecture.</span></li>\n <li><span>Assist in the development and implementation of innovative AI/ML solutions for proactive management of financial crimes compliance risks.</span></li>\n <li><span>Support cloud migration strategies for financial crimes compliance applications.</span></li>\n <li><span>Support the implementation and monitoring of controls for completeness, accuracy and timeliness of data, integrations and applications availability and performance.</span></li>\n</ul>\n<p><span><b><u>Required Qualifications</u></b></span></p>\n<ul>\n <li><span>A bachelor’s or master’s degree in computer science, engineering, data science, or a similar field of study.</span></li>\n <li><span>5-9 years of hands-on experience with data engineering, ETL development, and data warehousing.</span></li>\n <li><span>Solid experience with Big Data/Cloud Engineering and distributed processing (Batch and streaming concepts).</span></li>\n <li><span>Hands-on experience with AWS (Data platforms, Compute, Storage, Security, Process Orchestration and CI/CD).</span></li>\n <li><span>Proficient hands-on experience with Snowflake including Snowpark, Snow SQL, RBAC, Masking and Snowsight.</span></li>\n <li><span>Experience in implementing controls framework for enterprise-wide complex data and applications landscape.</span></li>\n <li><span>2-4 years of experience in financial crimes compliance or a related data-intensive field within a global organization.</span></li>\n <li><span>Hands-on experience with enterprise solutions development using Python for data manipulation and scripting.</span></li>\n <li><span>Familiarity with Large Language Models (LLMs) and their potential application in data analysis or compliance.</span></li>\n <li><span>Excellent communication, negotiation and stakeholder engagement skills to create consensus and build collaborative relationships.</span></li>\n</ul>",
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