Citi\'s Investor Services Technology group is seeking a technically exceptional and domain-savvyData Architectto serve as the definitive data architecture authority across the Investor Services (IS) program ? spanning Custody, Fund Administration, and Securities Finance.
This is explicitly ahands-on architect role. The successful candidate will be expected to write, review, and validate architecture artifacts, data models, canonical schemas, and technical standards. You will be embedded with delivery teams, working directly with business analysts, data engineers, and technology leads to produce production-quality data architecture outputs that the entire IS program depends on.
You will also lead the design and delivery of a suite ofdata architecture utilities? reusable tooling, accelerators, and automation that dramatically compress the time to deliver consistent, standards-compliant data integrations across Investor Services platforms. This role is a rare opportunity to set the data foundations for one of the most complex and consequential technology transformation programs in global financial services. Deep Custody and/or Fund Services domain knowledge is a prerequisite, not a preference.
Responsibilities:
Data Architecture Principles & Standards
Define, document, and own the Investor Services data publication architecture principles ? governing data modelling standards, naming conventions, versioning strategies, API data contracts, and data quality rules across all IS technology domains.
Architecture Pattern Standardization
Work with delivery leads across all 50+ IS platforms to define, document, and enforce standardized architecture patterns for data generation, transformation, and consumption ? covering batch, near-real-time, and event-driven data flows from source systems to downstream consumers.
Canonical Data Models & Dictionaries
Personally lead and contribute to the creation of canonical data models, enterprise data dictionaries, and business glossaries for Custody and Fund Services domains ? collaborating directly with business SMEs, operations leads, and delivery architects to reach consensus and lock down definitions.
Canonical Formats & Samples
Design and publish canonical message formats (JSON schemas, Avro), reference data samples, and integration contracts ? providing platform teams with unambiguous, implementation-ready data specifications that eliminate downstream interpretation risk.
Data Architecture Utilities
Design and build shared data architecture utilities ? including schema validators, data contract testing frameworks, data lineage trackers, canonical mapping accelerators, and code generators ? that compress individual platform delivery timelines and enforce standards automatically.
Business & Tech Collaboration
Serve as the primary bridge between business stakeholders and engineering teams on all data architecture decisions ? facilitating working sessions, reviewing data model proposals, resolving conflicts, and driving timely sign-off on data contracts across a complex, multi-stakeholder program.
Data Governance & Lineage
Establish data governance frameworks that cover data ownership, stewardship, classification, and lineage across IS platforms ? ensuring regulatory auditability, data quality SLAs, and compliance with internal data management policies and external regulations.
Program Timeline Acceleration
Proactively identify and remove data architecture bottlenecks that are blocking delivery across the IS program ? using utility tooling, pre-built reference architectures, and direct hands-on contribution to unblock platform teams and compress overall program timelines.
Experience:
- 10 - 12+ years in technology, with at least 6 years in a data architecture, data engineering, or enterprise architecture role within financial services
- Demonstrable track record as a hands-on data architect? directly authoring data models, schemas, and technical standards (not purely advisory)
- Experience defining data architectures for large-scale, multi-platform programs in a regulated financial institution
- Background working across complex, multi-stakeholder environments requiring negotiation and consensus-building on data definitions and contracts
- Experience delivering shared architectural tooling or utilities that improved delivery velocity at program scale
Education:
- Bachelor\'s or Master\'s degree in Computer Science, Information Systems, Engineering, or a related technical discipline
Technical Skills:
- Expert-level proficiency in data modelling techniques: conceptual, logical, and physical modelling; entity-relationship (ERD) design; dimensional and normalized models
- Deep expertise in canonical data format design: JSON Schema, Avro, ? including schema versioning, backward/forward compatibility, and evolution strategies
- Strong command of API design and data contract patterns: OpenAPI, AsyncAPI, consumer-driven contract testing (Pact)
- Hands-on experience with data lineage and cataloguing tools (Apache Atlas, Collibra, Alation, DataHub, or equivalent)
- Proficiency in event-driven architecture and messaging platforms: Apache Kafka (schema registry, Avro serialization), Solace
- Working knowledge of cloud data platforms: Databricks, Snowflake, AWS (Glue, Lake Formation), Azure (Data Factory, Synapse), or Google Cloud Platform
- Ability to read and write production-quality code in Python or Java ? sufficient to build and contribute to data architecture utilities
- Familiarity with data quality frameworks, master data management (MDM), and metadata management best practices
Domain Knowledge:
- Custody:Deep understanding of asset servicing data ? securities master, settlement instructions, positions, corporate actions, income events, and reconciliation data structures
- Fund Services:Working knowledge of fund accounting data models ? NAV components, expense structures, investor registers, transaction data, and fund reporting data requirements
- Familiarity with industry data standards and messaging protocols: SWIFT (MT/MX, ISO 20022), FIX, FpML, and their data model implications
- Understanding of securities reference data: instrument master, issuer data, pricing, and the data management challenges at global scale
- Knowledge of post-trade settlement data flows: DVP/FOP settlement, fail management, and the data hand-offs between custody and counterparty systems
- Awareness of regulatory data requirements: SFTR reporting data fields, FATCA/CRS data requirements, and audit trail obligations in custody and fund services
Education:
- Bachelor\'s degree or equivalent experience
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Job Family Group:
Technology
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Job Family:
Applications Development
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Time Type:
Full time
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Primary Location:
Jersey City New Jersey United States
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Primary Location Full Time Salary Range:
$176,720.00 - $265,080.00
In addition to salary, Citi?s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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Anticipated Posting Close Date:
Jan 26, 2027
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Automated Processing and AI
We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate\'s skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
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