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Data Solution Architect

Jobs post

  • Poland, Eastern Europe Location
  • EUR380 - EUR390 per day Salary
  • Data & Analytics Technology
  • Contract Type
  • Remote Workplace
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Data Solution Architect / Remote / 6 months / Start ASAP

Max Rates: Poland €390 per day /UK Inside IR35 £650 per day / Romania €455 per day / Spain €425 per day / Hungary €335 per day


The expected responsibilities of the Data Architect are:

* Define Data Structures & Data Flows to Meet Business needs. Specifically for OMO, progress an architectural design to bring data from multiple existing systems into a centralised data warehouse, building upon the existing data warehouse used within QDP. This will include defining:
* Data transmission and pipelines required to bring data into QDP
* Data modelling how the data will be held in QDP for each source scheme, understanding the existing QDP database design, and understand how data needs to be curated and accessed for OMO specifically for the data quality analysis
* Data modelling how we align data from different sources into a common schema that can be used for analysis and reporting, with focus on building a client centric view.
* Being able to work with existing 3rd party suppliers to assess and agree options for sourcing improved data feeds into the data warehouse.
* Design the data architecture to provide Data Quality monitoring, including trend analysis of issues resolved / new instances, and ability to report data quality across multiple systems for logical groupings of data (e.g. Client data, Adviser data, Payment data etc)
* Support strategic architecture design for mastering Customer data across the client.
* Carry out architectural review of legacy datasets and provide recommendations for Data Archiving, defining Archive standards, considering access requirements, data minimisation, retention etc
* Support data architecture assessment and design for the client strategic data estate, as the client embarks on a journey to move to a simplified data estate, and participate in design relating to key principles around data mastering and integrations.

Project Overview: Operating Model Optimisation - Data Initiatives:

The client is addressing, within the client Financial Planning (QFP) Advice business area, a legacy of data quality issues that are causing operational 'pain points' resulting in inefficient working practices, additional manual work arounds to address data issues and causing some infrequent technical failures of integrations due to invalid data. There are three main Practice Management systems used by Advisers in QFP, resulting in complex integrations and inconsistencies in data. The Data workstream will look to address differing levels of data quality between systems and to simplify MI and reporting.

This project is split into 3 workstreams, with the team working across all 3 workstreams:

1. Data Quality: Addressing data quality issues across the end-to-end Advice journey, with multiple systems in scope of data cleanse. This workstream will define the standardised data model for QFP Advice and perform data quality profiling to assess data quality within each data domain, defining treatment strategies to address issues and provide ongoing data quality scoring and reporting. Support is required to progress this workstream as follows:
a. Define and design a strategic data quality 'toolset' to take data feeds from multiple systems, perform data quality scoring, and produce reports on data quality at a number of levels (per business area, per adviser, per system etc). This will leverage the existing QDP data warehouse which uses DataBricks and ADF, with PowerBI used as the reporting layer.
b. Define and build data scoring reports for each data entity.
c. Analyse and investigate the data anomalies to define specific data quality focus areas for treatment.

2. Data Estate: Overall this workstream is investigating existing issues data integrations or inefficient data management and recommending technical changes to data feeds and front end UIs to better control data quality.


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