Director Data Architecture

Overview:
TheArchitect Aladdin Data Platforms & Servicesis asenior technical leaderwithin BlackRocksCentral Architectureorganization. This leaderisresponsible forshaping governing and advancing the architectureacross the entire portfolio of data platforms and shared services within theAladdin Dataorganization. The role blends deepexpertiseinplatform architecture enforcement ofenterprise standards anddeliveryaccountability. The Architect partners closely with platform engineering product management and operations teams to ensure theAladdin Data ecosystem evolves as a cohesive interoperable system. The goal is to translate architectural direction intomeasurable improvementsin system reliability scalability performance and developer productivity.Unlike strictly advisory architecture roles this position carries direct accountabilityfor delivering architectural outcomes and serves as the custodian of enterprise-widestandards design patterns and best practicesacross the Aladdin Data landscape.

Scope of Responsibility:
This roles influence spans theentire Aladdin Data portfolio including (but not limited to) the architecture of:

• Data Platforms and Frameworks:Systems and services fordata acquisition ingestion transformation data quality assurance (warranty) distribution and governance.

• Shared Services and APIs:Platform APIs/SDKs configuration models metadata management observability frameworks continuous integration/continuous deployment (CI/CD) and otheroperational toolingthat supports the Aladdin Data ecosystem.

• Data Processing Patterns:Batch and streaming data processing architectures includingETL/ELT pipelinesandevent-driven/streaming frameworks.

The Architectsownership is broad horizontal and cross-platform cutting across multiple systems and teams rather than being confined toa single productor application. This ensures consistent architectural practices and interoperability throughout the Aladdin Data organization.

Core Responsibilities:

1. Platform & Portfolio Architecture

• Define and evolve target-state architecturesfor all components of the Aladdin Data platforms and shared services portfolio guiding the ecosystem toward acohesive scalable and high-performance future state.

• Establish and socialize architectural principlesthat ensure interoperability modularity standards-based integration andoperational excellenceacross platforms.

• Own andmaintainarchitectural frameworks and contractsfor shared capabilities including:

• APIs and SDKs:Ensure consistent interface designs and usage patterns across services.

• Configuration & Metadata Standards:Define how systems describe configurations and metadata for uniformity and integration.

• Data Modeling Conventions:Develop canonical data models and patterns for how data is structured and managed across the platform.

2. Delivery of Architectural Outcomes (Not Just Advice)

• Translate architectural vision into tangible deliverablesby working closely with engineering and product teams. This includes guiding designs and implementations so that architecturalintent is realized in actual adopted platforms and features.

• Drive measurable improvementsin key platform metrics. For example deliver initiatives that:

• Reduce operational noise andimprove the reliabilityand stability of data platform services.

• Increase throughput and scalabilityof data processing for high-concurrency and high-volume workflows.

• Accelerate time-to-onboardfor new data pipelines products and domain datasets improving developer and user productivity.

• Remain deeply engaged throughout the delivery lifecycle frominitialdesign and development through to deployment rollout and user adoption.This is a hands-on leadership role not limited to providing guidance at a distance. The Architect will work side-by-side with teams to verify that architectural recommendations are effectively implemented and deliver the expected benefits.

3. Standards & Governance

• Codify andmaintainreference architectures design patterns and technical guardrailsfor all Aladdin Data platforms and services. This includesdocumenting best practicesandengineering standardsfor code quality testing release management security and observability.

• Lead architecture review boards and design governance processes ensuring a bias toward clear decision-making and the enforcement of agreed-upon architecture standards across projects and teams. Decisions are documented and followed up with concrete action items and compliance checks.

• Establish paved road development practices provide well-defined recommended patterns and frameworks that enable product and engineering teams to move quickly and safely. By offering these proven paths (for example standard templates common libraries or automated infrastructure) the Architect helps teams avoid reinventing solutions and ensures consistency across the enterprise.

4. Engineering Excellence & Enablement

• Mentor and develop engineering talentand junior architects. Champion modern data platform engineering practices such asDataOps robustCI/CD pipelines automated testing and performance tuning. Guide teams in designing for high availability fault tolerance and scalability.

• Drive a culture of continuous improvement and technical excellence.Identifysystemic gaps in tools processes or architectural approaches that hinder productivity or quality. Lead cross-platform initiatives to remediate these gaps such as introducing new development tools refining processes or improving documentation and training.

• Enable self-service and knowledge sharing.Work closely with teams to ensure they have the frameworks documentation and support needed to build andoperatedata products efficiently. This may involve creating architecture playbooks conducting training sessions andfacilitatingcommunities of practice.

Technology Expectations (Depth of Expertise):

The Architect must have deep hands-onexpertiseand the ability to set standards in several key technology areas:

• Snowflake & Advanced Data Warehousing:Extensive experience with the Snowflake platform including advanced capabilities such asDynamic Tables(e.g. understanding refresh semantics and data determinism and implementing effective monitoring and alerting for data freshness)streaming and change data capture (CDC) patternsfor near-real-time data processing use ofzero-copy cloningfor managing environments and safe experimentation andperformance tuning and scalabilitybest practices (optimizing warehouse sizing concurrency handling and ensuring operational reliability). The Architect should be able todefine enterprise-wide Snowflake usage standardsand patterns to ensure consistent safe and efficient adoption of Snowflake across multiple teams and data domains.

• Data Modeling & Transformation (dbt):Deepexpertisein data modeling methodologies and transformation frameworks. A strong preference is given to experience withdbt(data build tool) includingproficiencywithSQL-centric data modeling Jinja templating writing custom macrosdevelopingand using reusabledbtpackages implementing data quality tests and structuringdbtprojects for maintainability and collaboration. The Architect will shape and enforceconsistent modeling conventions and reusable transformation patternsacross the organization ensuring that data pipelines are well-documented tested and integrated into CI/CD processes for reliable deployments.

• Streaming & Event-Driven Architectures:Proven experience with modern streaming and real-time data processing technologies such asApache Kafka(event streaming schema management designing for fault-tolerance and delivery semantics) andApache Flinkor similar stream processing frameworks (stateful stream processing management of event time vs. processing time checkpointing and operationalizing streaming jobs). The Architect should be capable of designing and integratingevent-driven architecturesinto the broader Aladdin Data platform ensuring these real-time systems are incorporated with the firms standards fordata governance observability (monitoring & logging) data lineage and operational controls.

• Workflow Orchestration &DataOps:Strong background inworkflow orchestration systems(particularly directed acyclic graph (DAG)-driven orchestration tools for batch data pipelines) andDataOpsbest practices. Experience implementing and managing robust CI/CD pipelines and release management processes (e.g. using tools like Git Azure DevOps or similar) as well asestablishingcomprehensiveobservability practices(including audit logging health checks performance monitoring and alerting for data workflows). The Architect should also be skilled in developingstandardized operational runbooks playbooks and escalation proceduresto ensure that data platform servicesoperatereliably atscaleand that teams can effectively respond to incidents.

Qualifications:

• Experience:Minimum12 yearsof experience indata platform architecture data engineering or building large-scale distributed systems witha track recordof technical leadership in complex multi-team projects.

• Architecture Leadership:Demonstratedsuccess in definingenterprise or platform architecturesand driving the implementation of those architectures across multiple teams or product lines. Ability tobalance long-term strategic vision with practical delivery ensuring that architectural decisions lead to concrete improvements and business value.

• Technical Expertise:In-depth knowledge of modern data technologies and architecture patterns including relational and cloud-native data platforms big data processing streaming architectures and data integration techniques. Hands-onproficiencywith tools and languages relevant to the Aladdin Data tech stack (e.g. Snowflake Python/Java SQL Kafka Flinkdbt cloud infrastructure CI/CD pipelines).

• Leadership & Collaboration:Exceptional communication and interpersonal skills with theability to influence and align diverse stakeholdersfrom engineers and product managers to senior executivesin a matrixed organization. Comfortable driving decisions and building consensus without direct reporting authority usingexpertiseand persuasion.

• Industry Knowledge:Experience infinancial services or other highly regulated industriesis strongly preferred as it provides crucial understanding of data governance security requirements and operational rigor needed for success in the Aladdin environment.

Success Metrics:(Key Indicators of Success in this Role)
Success in the Architect Aladdin Data Platforms & Services role will bedemonstratedby:

• Unified Standards Adoption:Multiple platform teams embrace and implement shared architecture standardssuch as common APIs consistent data modeling patterns uniform CI/CD pipelines and robust operational controls. This results in ameasurable reduction in platform fragmentationand duplication of effort across Aladdin Data teams.

• Scalable & Reliable Snowflake Deployment:Snowflake usage grows significantly and safely across both batch and near-real-time workloads.The architects guidelines enable teams toleverageadvanced Snowflake features (dynamic tables performance tuning zero-copy cloning) effectively leading toimproved concurrency handling enhanced system reliability and well-governed environment managementfor data experimentation.

• Enterprise-WidedbtStandardization:dbtisestablishedas a consistent governed standard for data transformationacross the organization. Teams areusingreusabledbtpackages standardized Jinja templates and shared data modeling best practices which drive higher developer productivity better data quality and simpler onboarding for new data products.

• Integrated Streaming Ecosystem:Real-time streaming capabilities (e.g. Kafka Flink) are seamlessly integratedinto the broader Aladdin Data platform supported byappropriateoperationalguardrailsmonitoring and data governance. Teams can confidently implement event-driven architectures with consistent patterns for data lineage observability and resilience expanding Aladdins ability to handle both batch and streaming data demands.