Job Summary:
As a top-25 U.S. commercial bank, Pinnacle operates under intense regulatory scrutiny - DFAST, CCAR, Basel III/IV, FR Y-14, Call Report, and a growing suite of emerging requirements from the OCC, FDIC, and Federal Reserve. This role exists to build and own the data foundation that makes those obligations sustainable.
You will be the authoritative technical voice on regulatory data products - designing, engineering, and governing Databricks-based data products that feed our regulatory calculation engine (Wolters Kluwer AXIOM) and downstream reporting estate. Simultaneously, you will be a key driver of AXIOM platform health: optimising data feeds, maintaining calculation logic, and partnering with Finance and Risk to translate regulatory change into platform updates before deadlines create risk.
Job Duties and Responsibilities:
Regulatory Reporting Data Products & AXIOM
- Design, build, and own Databricks data products that serve as the authoritative, governed source of regulatory data feeding AXIOM - covering DFAST/CCAR, Basel III/IV capital calculations, FR Y-14 A/B/C, Call Report (FFIEC 031/041), FRTB, and LCR/NSFR.
- Architect and maintain end-to-end data lineage from source systems of record through transformation layers to AXIOM ingestion points and regulatory submission - with full auditability and point-in-time reproducibility.
- Own the AXIOM data interface layer: design and manage the data feeds, staging structures, and transformation logic that populate AXIOM inputs; troubleshoot feed failures and calculation anomalies in close partnership with Finance and Risk technology.
- Maintain and evolve AXIOM calculation configurations as regulatory requirements change - working with Finance, Risk, and Compliance to translate rule changes (Basel IV, FRTB phase-in, FR Y-14 revisions) into platform updates.
- Define and implement data quality frameworks, validation rules, and reconciliation controls integrated into regulatory data pipelines - with automated alerting and escalation paths.
- Support regulatory examinations and internal audit by producing and maintaining data lineage artefacts, control evidence, and architecture documentation.
- Engage proactively with emerging regulatory requirements and translate them into data product and AXIOM configuration changes before deadlines create risk.
Databricks Data Product Engineering
- Build and own production-grade Databricks data products on Delta Lake / Unity Catalog - including medallion architecture (bronze/silver/gold), certified datasets, SLA-backed pipelines, and formal data product contracts.
- Engineer Delta Live Tables (DLT) pipelines for regulatory data ingestion and transformation - implementing incremental processing, CDC patterns, and expectations-based data quality enforcement.
- Apply Data Vault 2.0 and dimensional modelling patterns where appropriate to build regulatory data models that are auditable, historised, and resilient to source system changes.
- Leverage Databricks Asset Bundles and CI/CD patterns (Azure DevOps) to manage pipeline deployments, environment promotion, and change control across dev/test/prod.
- Design and implement Databricks SQL serving layers that enable Finance, Risk, and Compliance to self-serve regulatory data with appropriate row-level security and access controls via Unity Catalog.
- Instrument pipelines with observability tooling (pipeline monitoring, data quality dashboards, SLA alerting) so regulatory data health is visible and measurable at all times.
- Partner with Enterprise Architecture on integration patterns (CDC, event-driven, micro-batch) and ensure regulatory data products conform to Pinnacle''s broader Azure cloud architecture standards.
Orchestration & Platform Operations
- Design and manage production orchestration for regulatory pipelines on Astronomer (Apache Airflow) - DAG design patterns, dependency management, SLA monitoring, and operational runbooks.
- Lead the migration of regulatory workloads off legacy platforms (Control-M, SSIS, DataStage) onto the modern data estate - defining wave plans and guardrails that avoid disrupting live reporting cycles.
- Manage pipeline reliability for regulatory submissions: on-call escalation support during close periods, root-cause analysis for incidents, and systematic remediation.
- Establish Power BI semantic layer standards for regulatory and management reporting - certified datasets, composite models, row-level security - replacing Business Objects universes and Crystal Reports.
Data Governance & Standards
- Define and enforce data architecture and data product standards across regulatory data domains - ingestion, storage, transformation, serving, and consumption.
- Establish metadata management and data cataloguing practices using Azure Purview / Microsoft Fabric Data Governance in conjunction with Databricks Unity Catalog, with particular emphasis on regulatory data lineage and classification.
- Partner with the Enterprise Data Governance team to apply BCBS 239 principles to regulatory data products - ensuring data accuracy, completeness, timeliness, and adaptability are formally measured and reported.
- Lead architecture and data product reviews for new regulatory data initiatives, evaluating designs against compliance, security, scalability, and TCO criteria.
Stakeholder Engagement & Leadership
- Serve as the primary technical point of contact for Finance, Risk, and Compliance on all regulatory data and AXIOM matters - translating business requirements into data product designs and communicating trade-offs clearly.
- Mentor data engineers and BI developers on Databricks data product patterns, DLT pipeline design, and regulatory data standards.
- Engage Wolters Kluwer (AXIOM), Databricks, Microsoft, and Astronomer as platform partners - managing vendor relationships, escalating product issues, and influencing roadmaps where Pinnacle''s scale warrants it.
- Communicate data lineage, quality, and architecture posture to internal audit, regulators, and executive stakeholders in plain business terms.
The information on this description has been designed to indicate the general nature and level of work performed by employees within this classification. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job
Pinnacle is an Equal Opportunity Employer committed to fostering an inclusive work environment.
Minimum Education: Bachelor''s Degree required in Computer Science, Information Systems, or related field.
Minimum Experience:7+ years of data engineering or data architecture experience, with at least 4 years in financial services, banking, or a similarly regulated environment.
Required Knowledge, Skills & Abilities:
- Demonstrated hands-on experience building production data pipelines and data products that directly support regulatory reporting - any of: DFAST, CCAR, Basel, Call Report, LCR/NSFR, FR Y-14.
- Deep hands-on expertise with Databricks - Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, and Databricks Asset Bundles or equivalent CI/CD patterns for pipeline deployment.
- Direct experience working with AXIOM (Wolters Kluwer): data feed design and management, staging layer configuration, calculation module familiarity, and troubleshooting feed or calculation issues.
- Strong Azure data platform experience - ADLS Gen2, Azure Data Factory, Azure Synapse, Entra ID / RBAC, Azure Key Vault, and networking controls relevant to regulated data environments.
- Solid data modelling skills - Data Vault 2.0, dimensional modelling, and relational normalisation; ability to select and apply the right pattern by regulatory use case.
- Hands-on experience with Apache Airflow or Astronomer for production-grade pipeline orchestration in a regulated environment.
- Working knowledge of data lineage, data quality frameworks, and metadata management - able to build and operate these controls, not just specify them.
- Experience migrating workloads off legacy ETL/orchestration platforms (SSIS, DataStage, Control-M, or equivalent).
- Strong written and verbal communication - able to produce clear data lineage documentation, present to auditors and regulators, and translate technical complexity for Finance and Risk stakeholders.
Platform Landscape
This role spans both sides of a major platform transition:
Capability
Legacy (Retiring)
Modern Target State
Integration / ETL
DataStage, SSIS
Databricks (Delta Live Tables), dbt
Orchestration
Control-M
Astronomer (Apache Airflow)
Reporting / BI
Business Objects, Crystal Reports
Power BI Premium, Databricks SQL
Storage / Compute
On-prem SQL / SAN
Azure Data Lake Gen2, Databricks Lakehouse
Governance
Manual / disparate
Unity Catalog, Azure Purview, Microsoft Fabric
Regulatory Calc Engine
AXIOM (Wolters Kluwer)
Axiom modernization + Databricks data products
Preferred Qualifications
- Familiarity with BCBS 239 principles and their practical application to bank regulatory data architecture.
- Experience with dbt, Great Expectations / Soda, or Monte Carlo for transformation testing and data observability on Databricks.
- Knowledge of FIS core banking platform data structures and integration patterns into the regulatory data estate.
- Exposure to real-time or near-real-time architecture patterns (Event Hubs, Kafka, Spark Structured Streaming) for operational risk or treasury liquidity reporting.
- Experience with Power BI at scale - semantic layer design, Premium capacity management, and migration from legacy BI platforms.
- Knowledge of model risk management requirements (SR 11-7 / OCC 2011-12) as they apply to analytical models used in regulatory capital calculations.
- Relevant certifications: Databricks Certified Data Engineer Professional, Microsoft Certified: Azure Data Engineer Associate, or equivalent.