University of Cambridge

Designing and Building (loading) Data Warehouses, BI Solutions, Enterprise Data Architect, Lead Data Architect

London, London, United Kingdom

Senior Data Designer.  Designing the Logical/Physical Dimensional Model (set of Data Marts) for the new NewDay data platform based on AWS.  Design and development of the NewDay Own-Brand credit card data, currently hosted onsite on SQL Server and Co-Brand credit card data, currently hosted off-site on Oracle.  Data sourced from disparate sources including Application data, day-to-day Account data as well as together with the transactional data from First Data – a credit card merchant services company.  In addition, Bureau data from Experian, Call Credit etc. received both daily and monthly. Aggregate design based on user requirements at both a month-end and cycle-end (payment day) basis.Data Lake creation for NewDay.  100+ Interface files ingested into the Data Lake for the Own-Brand data sources and a similar number for Co-Brand data of the Data Lake for a Big Data DW Solution.  Notable aspects of project: Big Data, AWS, Spark SQL, Data Lake, Athena, Python, Dremio, ERWin•	Data Mart - Design of Logical/Physical Dimensional Models (Kimball) based on the user requirements and on their usage patterns.  Developing Design Standards - Source-To-Target Mapping documents driving the first-cut automated build of the ETL code, logical transformation design as well as Avro transformation design and conformance of incoming data.  GDPR/Privacy considerations.  •	Data Lake - Design Authority for all Mapping Documents, Data Models and Data related artefacts on the Project.  100+ Interface files ingested into the Data Lake for the Own-Brand data sources and a similar number for Co-Brand data.  Data conformance.  Introducing naming standards.•	Design of aggregates for Account, Transactional and other behaviours in conjunction with the various internal teams including Credit Risk, Marketing etc.  based on the new Data Mart structures as well as the enhanced Business processes.

New Day ltd

Senior Data Designer – Lead Data Architect

Lead Data Architect.  Data Platforming Provisioning (DPP) within Sainsbury’s. Initially building a Customer centric Data Warehousing Solution for Marketing & Innovation within Sainsbury’s. Project was under NDA.  Creating a Data Lake to feed Sainsbury’s requirements across the board in support of the Retail activity. GDPR for Marketing, Product Range Planning etc. Part II.  Data Lake creation for Sainsbury’s Bank.   100+ sources – 1000+ Files to be ingested into the Data Lake.  Banking, Credit Cards, Loans, Customer Profiling Data, Mortgages, Car, Pet & Home Insurance etc.  Additionally, bringing on board a subset of the Data Lake for a Big Data DW Solution.  Banking Reporting & Compliance requirements.Notable aspects of project: Big Data, Hadoop, Hive, Impala, Data Lake•	Design of Logical Dimensional Models (Kimball) based on the requirements.  In addition, this ‘purist’ model was optimised for Hive/Impala implementation in a Hadoop environment. Using Parquet and Avro data formats. Flattening the Dimensional Model based on User requirements and usage patterns.•	Data Partitioning and Bucketing Strategies in Hadoop/Hive for performance.  Data Lake design using AWS S3 environment.•	Feeding a team of 20+ Data Analysts with Data Artefacts.•	Developing Design Standards - Source-To-Target Mapping documents, Data Models Enterprise Data Model feeding into SOR Enterprise standards. GDPR/Privacy considerations.•	Design Authority for all Mapping Documents, Data Models and Data related artefacts on the DPP Project.  Merging data from disparate sources.  100+ Sources & 1000+ files ingested into the Data Lake. •	Development of the Enterprise Canonical Data Model based on the newly implemented Business processes.•	Design of 3rd Normal Form Integration Layer based on the newly implemented Business processes and data sources.•	Supporting near Real-time Data Movement supported via data architecture allowing for ingestion and movement across layers in an orderly fashion.

Sainsbury's

Lead Big Data - Data Architect - Architecture Team

Enterprise Data Architect.  Canonical Data Models for Integration Projects across the Reed Exhibitions application landscape including: Oracle E-Business Suite, Customer Data Hub, Salesforce, Master Data Management and Enterprise reporting.   Some 15 plus applications are providing an ‘integrated’ solution to Reed’s IT needs.  Liasing with third-party companies producing the integration software.  Design and delivery of a Data Vault solution for the Data Migration by Business Unit designing in re-usability.Notable aspects of project:•	Development of the Enterprise Canonical Data Model based on the newly implemented Business processes as well as a federated Salesforce application and other applications.•	Implement (Physicalise)  logical designs in the Data Migration and other solutions.  Design a Common Interface (CIM) Model as a Data Vault model/database with target application key management capabilities to facilitate the loading of data across multiple applications to support integration at go-live. Identify Data Quality issues across applications.•	Collaborate with subject matter experts, business analysts, data analysts and third-party companies create and add to the Enterprise Data model.  •	Review Data Models (3rd Normal form, Kimball as well as transient and application specific data models) produced by third-party suppliers ensuring that best-practice is followed in all Data Modelling and general Data Architectural considerations in particular the Data Warehousing solutions.

Reed Exhibitions

Enterprie Data Architect - Architecture Team

Enterprise Data Architect.  Providing consultancy, development, architecture and operational services to more than 25 global retail markets and clients.  Delivering a truly unique, world class capability driving the increase in growth and retention of customer loyalty programmes on behalf of a number of major retail clients.  A very data intense environment - processing around a billion rows of data per week contributing to a timely, integral, accurate publication and persistence around 200TB of production data.  The Dunnhumby Common Data Model (CDM) provides a common solution to a number of retailers including Tesco, Krogers and Macys. Notable aspects of project:•	Ownership of the final design of data models at the logical and physical levels and for the development and maintenance of existing enterprise (CDM) models.•	Provide solutions for complex information modelling and architectural problems.  Develop Kimball models including snowflakes, irregular dimensions, and surrogate, compound and intelligent keys to solve problems.•	Collaborate with subject matter experts, business analysts, data analysts and other data modellers to create data modelling deliverables through new data models or extending existing Enterprise models.  Communicating complex technical subject matter to audiences with widely differing levels of knowledge and experience.•	Review business requirements and profile sample data to gain further insight for the purpose of designing data models at the logical levels and physical levels.•	Provide support in the use of enterprise data, including guidance in understanding and exploitation of the underlying data and business models, and identifying optimal data sourcing, mapping and querying methods.•	Mentoring less experienced members of the CDM Team.  Defining ‘Best Practice’ for all Data and Database related issues.

dunnhumby

Enterprise Data Architect - Business Model Reviewer

Data Architect and SSIS Developer.  The design and build of a Quotes Data Mart based on the Quote Canonical Data Models as well as ‘Quote’ feeds from the operational systems. SSIS job design and development to populate the data Mart above.  The mart was designed and built using Agile Design principles. Notable aspects of project:•	Design of Quotes Data Mart based on the Canonical Data Models/OLTP (as Conceptual Data Model) and Data Feeds generated by the ‘Quotes Engine’ (Operational Systems).•	Data Analysis of the Operational OLTP Models and Data Feeds to arrive at a Data Mart Design.  •	SQL Server 2008 – Stored Procedures to interrogate the XML Quotes Data.•	SQL Server 2008 – SSIS Job design to populate the Quotes Data Mart.•	SQL Server 2008 – Optimise SSIS Job design to meet SLAs (overnight processing window).•	Identifying and resolving Data Design and Data Quality issues – feedback into Canonical Data Model.•	Defining ‘Best Practice’ for all Data and Database related issues. Defining Data Governance and Data Standards for Reference Data, Design Artefacts and ownership rules.

Data Warehouse Architect and ETL Developer

Trainer in DataStageDelivering DataStage for IBM.

Trainer in DataStage

Enterprise Data Architect. Design Authority on Integration, New Functionality and Enterprise Reporting projects.  Salesforce Integration and definition work aligning Business Units globally. Data Integration between Websites (500+ sites maintained), Sales Order Processing Systems and Group reporting via the new Enterprise Data Warehouse designed and built using Agile principles. Notable aspects of project:•	Design workshops for the Data Warehouse and OLTP - Operational (CRM, SOP and Websites) Systems.•	Conceptual (Business) Data Models for business data & process definitions.•	SOA Integration Architecture – review and Canonical Form Model definition.•	Enterprise Data Warehouse Data Models – Kimball based schema using Agile design principles.•	Extensions to ‘out-of-the-box’ Salesforce.•	Quality Assurance of Physical Data Models (3NF) for all Databases.  •	Ensuring ‘Best Practice’ is followed in all Data and Database related issues. Defining Data Governance and Data Standards for Reference Data, Design Artefacts and ownership rules.

Enterprise Data Architect

Tokio Marine HCC is a speciality insurance provider – Lloyds market. Design the Premiums Data Mart on the new Enterprise Data Warehouse reporting solution.  Design Data Marts (Kimball Models) from the Operational Data Store (ODS) holding all of the HCC data covering all aspects of the HCC business covering premiums, claims, policies etc. Notable aspects of project:•	Design workshops for the Data Warehouse design and validating the Operational Data Store ODS design.•	Delivered a detailed Data Warhouse design.•	Review the ODS design which was based on Anchor modelling principles•	Producing detailed Source-to-target mappings to be used in the migration of data from the ODS to the Data Marts.•	Ensuring ‘Best Practice’ is followed in all Data and Database issues.

HCC Insurance

Data Warehouse Architect

TESCO Compare Migration. The migration of the TESCO Compare website from an RBS hosted environment using SQL Server 2008 and SSIS.  A consultancy (with an offshore presence) was charged with the actual development of the integrated Website and associated applications (e.g. CRM, Data Warehouse etc.) My role was to QA all aspects of the Design, Build and Data Migration of the Tesco Compare Databases and DW reporting. Notable aspects of project:•	Design workshops for the Data Warehouse and OLTP - Operational Systems.  Quality Assurance of Physical Data Models (3NF) for all Databases.  Demonstrating the viability of the Data Models produced to the Tesco Compare business.•	Design & Review the ETL Architecture - ETL Design and the detailed Source-to-target mappings to be used in the migration of data from the old systems to the new systems.  •	Development of a Data Migration Strategy & Data Migration Requirements for all systems.•	Ensuring ‘Best Practice’ is followed in all Data and Database related issues. •	Development of the Data Migration Test Strategy & the Data Warehouse Test Strategy, Daily Batch processing and Aggregation Build •	Taking all Data Warehouse and operational Database related documentation through to the Tesco Bank Design Authority sign-off.•	SQL Server 2008 – SSIS reviews as well as detailed analysis of the ‘Exception’ data to ensure that a minimal set of valid data is dropped when filtering bad data during the Data Migration.

Tesco Compare

Enterprise Data Architect / Data Migration Architect

Munich-Re Electronic Underwriting (EUR) Data Warehouse. Implement a Data Warehouse to be used for reporting on the Electronic Underwriting (Life) business.  The emphasis is on improving the quality of the Underwriting Straight-Through Process (STP) and improving the percentage of Policies that do not require manual underwriting by improving the quality of the Rules in the Underwriting Engine. Notable aspects of project:•	Development of Data Warehouse Architecture based on existing constraints.•	Development of Data Architecture.  Logical and Physical Data Models (3NF) using ERWIN.•	Conduct Requirements Elicitation Workshops.  Define & Confirm Reporting Requirements of the Electronic Underwriting business area with SMEs.•	Demonstrating the viability of the Data Models produced.  Proof of Concept for the Architectural decisions.•	Alignment with the ACORD (Insurance) Data Standards.•	Development of ETL Architecture for DataStage to cope with 50+ Partner Sources, including Error Handling, Audit Trails, Load Process Management and Master Data Management.•	Design of Common Interface Staging Area & ETL Source-to-target mapping to populate the DW as per Physical design above. •	Data Profiling.  Testing and Quality Assurance of the Source Feeds and ETL outputs.  •	Specification and Development of Oracle Stored Procedures in PL/SQL.•	Master Data and ETL Reference Data Management.

Munich Re

Technical Data Warehouse Architect

NORDEA – BASEL II Data Warehouse / integration project. The integration of data from the Scandinavian countries Denmark, Norway, Sweden and Finland to produce BASEL II compliant risk reporting for Nordea Bank.  Notable aspects of project:•	ETL Architect Design including Error handling, Audit and Reconciliation pieces.•	Development of ETL Jobs, Sequences and Routines using DataStage Server.•	Analysis of Interface Data (Feeds) and QA of ETL Source-to-Target mappings.•	Data Profiling.  Testing and Quality Assurance of the Source Feeds and ETL outputs.  Resolution of Data issues via enhancement of code specification.•	Master Data Management.  •	Load Process management (row counts) and Business Data Reconciliation. •	Incorporation of Audit Trails for Compliance reasons. •	Optimization of slow running Datastage Jobs.  Meeting agreed performance SLA targets.•	Error management and resolution. Reporting Errors by Nature/Severity/Interface•	Defect Identification, Prioritisation and Resolution (TEST Director).  •	Estimate and agree development plans with PM. Work Planning and Resource estimation.

Nordea

DataStage Architect/ Senior DataStage Developer

DHL – SAP integration project. The billing systems of six companies (within DHL France) were integrated to a SAP target.  The project was to develop an architecture that could be rapidly deployed in the numerous companies (in various countries) that have become part of DHL.  The integration of the companies’ billing systems was seen as the primary goal of the exercise.  The defined architecture was then used as a basis for a similar integration of the remaining European countries into a SAP Business Warehouse.    Notable aspects of project:•	Design of Architectural Components for handling multiple currencies, Re-processing Errors and Reconciliation for 21 Interfaces within the General Billing Interface (GBI – SAP) Area. Value of Invoices approx. 6 Billion Euros.•	Project Manager/Team Leader for a team of 9 developers. Planning/Coordinating their work.•	Defect Resolution. Estimate and allocate work to team. Resource planning.•	Design of Common Structural Targets (in SAP) for the ETL team. (Systems Analysis)•	Analysis of Interface Data (Feeds) & development of ETL mappings for DataStage developers.•	Configuring the TEST system.  Release management to TEST/PRODUCTION environments.•	Running the TESTING/GBI Team, liasing with BAs and general Project Management.•	Development of ETL Jobs, Sequences and Routines using DataStage Server.•	Derivation, Definition and Documentation of processing specifications.  •	Review and Optimization of slow running Datastage Jobs.  Meeting SLAs.•	Production support (3rd Level) for France and Denmark GBI Areas.•	Quality Assurance of the ETL output for the SAP Target.

Jaswinder Panesar

Jaswinder Panesar