SUMMARY:

• Results oriented leader with solid strategic skills in enterprise data technologies, advanced analytics, governed data lakes, data modelling, data catalogues, semantics architectures, data governance and data management. With a solid client - centered approach, deep business domain and data technology delivery skills, Konstantine regularly interacts at the executive, management and staff levels to deliver on data strategy, advanced analytics enablement and data lifecycle management across front, middle and back-office operations.
• Background includes development, implementation and management of enterprise digital data solutions by balancing the demands for agility and discovery with the need for curation and optimization for data analysis, data governance and data quality, delivered over multiple channels, users, roles and networks. Expertly directs resources, technology and expenses while being an SME for governed cloud-enabled data lakes, hybrid architectures, data catalogues and models, MDM, metadata and lineage, data governance, data profiling and quality scoring for data source, streaming data ingestion, data science, pattern discovery, machine learning, dashboards and BI reporting.
• Expertise across global markets in insight creation for customer and product profitability, risk and finance, BCBS239, RDARR, data reconciliation, asset management, treasury and liquidity, underwriting and claims management across financial services, insurance and information management industries.
• A leader in the development and implementation of industry assets where as the architect for Confidential Banking Data Warehouse/FSDM led an expansion phase of capabilities to include business content for risk management of complex financial instruments, asset and wealth management, compliance, profitability and liquidity management.
• A semantic tier accessing data in multiple data stores and structures such as external files, tables, in-memory and database links and metadata driven monitoring for performance and security management
• Domain semantic modeling build on FIBO, Confidential FSDM, Oracle FSDF, other data models,
• Cognitive mapping process with Cambridge Semantics (CS) ASDL to generate ontology and ETL code,
• Automated model enrichment based on learned structures, newly discovered concepts and modeler input
• Data source based on structural, referential and semantic consistency CS ASDL-AnzoGraph
• Ontology enrichment via feedback of newly discovered relationships, entities and transformations.
• Transformation code decomposition to atomic and derived data elements, and SPARQL code generation
• ETL specifications for non-RDF databases and traditional ETL tools such as Informatica, Infosphere Datastage, AbInitio, etc.
• Full lineage, SQL and processing logic, from data source to models and from models to data consumers
• Hybrid, message-oriented data architecture and integration, common data model and semantics, critical data element identification, data governance,
• Ingestion of entire data sources, data tagging and data conformity by domains and domain-based common data pipelines, role-based security,
• Metadata driven Business Information Model linking data hub content to common definitions, governed aggregations, governance, quality rules and physical data models
• Establishment of CDE authoritative data sources/ownership and lineage
• Common Data Model, Finance and Risk master data, transaction based standard data flows and data SLAs
• Realignment of 680 FTEs and a save of USD65 million in operational costs and retirement of Finance legacy app computational components and deployment into the data lake (Cash flows, FX calc. and Finance metrics), approximate saving USD14 million
• Build a data catalogue for standardized definitions, canonical data model based on Confidential IIW and ACCORD. Standardized data sourcing interfaces through metadata discovery and semantics modeling.
• Build a business glossary and business rules to remove the ambiguity in data sourcing from underwriting, risk and cash-flow systems.
• Delivered underwriting, policy, claims, payments and asset data into an IIW based core model implemented in a Hadoop data lake.
• Delivered BI and dashboards with abilities to aggregate and report atomic level data across domains
• Realignment of 175 FTEs and a save of USD35 million in HR costs. Sunset of manual reconciliation, aggregation processes and risk legacy applications with a savings of over USD25 million.
• Stakeholder management via a combination of Agile/Pilot methodology to fully align data, functional, quality and governance requirements across business units(BU) and group standards
• Designed, marketed and implemented the Group Common Data Architecture, by building the Group Data Hub and BU data lakes, with end to end metadata, data governance, quality and performance metrics
• Build a near real time BU G/L balances to group G/L balances mapping and reconciliation process
• Delivered a semantics based data architecture, integration framework, common data model and common data flows, a Business Information Model linked to data lake content with common definitions contains, business, governance, quality rules and metrics
• Build common data interfaces for local and group GL mapping/reconciliation, sourcing to downstream applications for BCBS 239, RDA, LCR, GSIB Reporting, Statutory reporting on IFRS, GDPR, FATCA, and Profitability for business unit, product and customer

TECHNICAL SKILLS:

Big Data: - Hadoop/HDFS/Hive, (Cloudera, Hortonworks), Sparc, Python, Apache Kafka, Cambridge Semantics

Advanced Analytics/visualization: - Watson Developer Cloud, Algorithmia, SAS VA, QlikView, Tableau, Cognos/TM1

Semantics and metadata management: - Collibra, Cambridge Semantics, Confidential Metadata Workbench, Business Glossary, Adaptive Software

Financial Management Suites, ERP Software: Oracle OFSA, SAP

Architectures: - Zachman Framework, TOGAF, Hybrid data architectures, Corporate Data Factory, Dimensional and SoR

Industry Data Models: - Confidential BDW/IIW, Teradata FSLDM, Oracle OFSAA

Data Integration: Infosphere Data Stage, MAP-R, Pentaho PDI, Informatica, MDM - Infosphere MDM

Database Management: - Modeling on Erwin, Data Architect, Mega, DBMS - DB2, Oracle, Teradata, Hive, MongoDB, Graph, Hbase, Neo4jloud Management - AmazonCloud enablement: - AWS, Google Cloud Platform

PROFESSIONAL EXPERIENCE:

Confidential

Responsibilities:

• Core data foundation - multi-tiered data lake and integrated streaming and batch pipelines - data integration architecture using MQ-Series, Kafka, AbInitio, Pentaho RAML, JSON and Python, critical data element identification and metadata management - Collibra, HCatalogue, Java - support fast ingestion of rapidly shifting data into a data hub organized by a Staged Data, Core Data, Common Information, MDM and virtualization layers.
• Governance framework enabling mapping of business requirements to solution components via metadata (Hadoop, Pentaho, HDFS/Hive, Qlick, Plateau)
• Establishment of authoritative data sources and approved data provisioning points for CDEs by use of quality score and governance completeness
• MDM and data standardized processing, common data model, common consumption layer, and data sharing SLAs. Risk and Finance Common Data Model using industry standard structures supports the Core Data and Common Information layers
• Identification of critical data elements, for profitability, funding, PPNR, GDPR, BCBS 239, LCR accelerated by Confidential ’s FSDM, and development of a core Business Information Model - the foundation of corporate data landscape for reporting, analytics, machine learning and algorithmic processing
• Group and business line levels data councils and working groups, operating model and organization structures, roles and responsibilities for data ownership/stewardship ingestion, integration, persistence, visualization and reporting
• Micro-service based, native connectivity and streamlined data pipelines ingest at entire source system level, tag and curate by domain, data at granular and aggregated levels including position, account, counterparty, instrument, event, transaction, asset, liability, collateral, cash flow and ledge balances.
• Data catalog drives BI, dashboards and discovery- the Business Information Model - stored in Collibra consists of a Common Data Model based on Confidential ’s BDW and is linked to a metadata-driven semantic layer of physical lineage, business terms and definitions, quality, governance and ownership rules, role based security model and operational metadata.

Confidential

Responsibilities:

• Prioritized a set of projects to implement tactical quick-wins while architecting a strategic target architecture and operating model
• Identified Critical Data Elements, policy, standards, source systems, data flows and data models and designed a method to identify and certify authoritative data sources by using data quality, governance and metadata metrics
• Designed CDO responsibilities for marketing of data, data ownership and stewardship, policies, standards, processes, roles and responsibilities and data quality workflow.
• Delivered the target state architecture and PoCs in retail and asset management including a multi-tiered common data model of intra-day and end-of-day atomic level data for party, assets, transactions, events and positions including deposit, lending and capital markets.
• Implemented a metadata driven data integration process, a semantics based data distribution layer and a common information layer supporting calculations/risk engines, analytics/reporting and feedback.
• Data catalogue - a Business Information Model (BIM) as the authoritative core data foundation with complete end-to-end lineage of critical data elements linked to data sources, data flows, profiling, integration, persistence, distribution and feedback. The BIM functions as the central managing point for BI, reporting and dishoards as well as facilitating data controls such as data issue resolution workflow to improve availability and quality of data within the bank.

Confidential

Responsibilities:

• Achieve full alignment for data, functional, and governance requirements across business areas, group functions and bank-wide MIS systems.
• Integrated Common data foundation provides data to BCBS 239, Risk Data Aggregation (RDA), Liquidity Capital management (LCR), GSIB Reporting, Statutory reporting - FATCA, FINREP- and Profitability for product and customer across the business.
• Effort is structured into data, analytics and infrastructure work streams with a tight partnership between business, IT, internal and external strategic partners
• Common business requirements identification and analysis, detailed integration architecture including canonical data modeling using Teradata FSDM and Confidential IFW/FSDM

Confidential

Responsibilities:

• Identified and qualified authoritative data sources within the significantly complex underwriting, reinsurance and risk management landscape
• Build a Business Information Model (BIM) to remove the ambiguity about data from underwriting, risk and cash-flow systems and function as the data catalog for accurate and semantically consistent BI analytics.
• Designed and rolled-out an ownership and stewardship model as part of data governance program
• Designed a canonical data model based on Confidential IIW and Industry standards for risk types - insurance (man-made, nat-cat) market, credit and operational, and asset positions in investments and alternative investments in hedge funds.
• Built an MDM and data management capability for geographic regions, all lines of business, products, positions, divisions and profit centers as well as assets and investments
• Standardized data sourcing interfaces derived via metadata discovery and semantics modeling.

Confidential

Responsibilities:

• Managed an effort and lead the design of a solution to collect analyze and report consistent trade common data across the investment operations. As an imperative business requirement trade volumetrics is major cost, resource utilization and forecasting driver.
• Identified all trade data flows across investment operations including equity, fixed income, loans, derivatives and options trading platforms.
• Identified CDEs to enable consistent management of transactions for regulatory compliance including Basel Accords and statutory reporting
• Identified authoritative source of information from disparate trade sources and merged historical and current information to enable Operations and Compliance to focus on analysis and judgment - rather than processing data.
• Designed a core data model for all trade flows including parties, positions, events, trade lifecycle including cancels/corrects, master and data
• Delivered ETL to extract and transform trade volumetrics and link to operational factors such as time to execute and best price to satisfy regulations and reporting

Confidential

Lead data architect and data warehouse delivery lead

Responsibilities:

• For a tier 1 global bank developed business data requirements development for Liquidity Risk Management and AML solution and regulatory compliance analytics and reporting using Cognos BI platform
• Implemented a user-driven enterprise data collection, integration and aggregation of data sources from across the firm, including core banking applications, trading platforms accounting subsystems, customer information, /master data and external data sources.
• Modeled and implemented the core data model based on BDW and DB2/UDB.
• Delivered metadata driven data integration, based on Infosphere and C++ extensions
• Data governance and quality based metrics for data stewards, and data councils in the Liquidity risk management and AML solution.
• Identified and qualified authoritative data sources within the significantly complex data landscape by use of data profiling and ownership factors and metrics
• Modeled and implemented the Basel I risk/finance core data model based on BDW and DB2/UDB.
• Produced ETL mapping documents including lineage and translation of business rules to ETL code
• Quality assured and supported the development of solution and provided SME support in global production rollout