Data Architect

Work with business leads and systems implementation partners

Define database/data warehousing requirements and data interfaces.

Conduct data model reviews with project team members/business subject matter experts.

Data Security, Management and Engineering Excellence

Build data security, management and engineering excellence into all solutions.

Consult with internal teams and client stakeholders on proposed solutions and how they’ll be developed/deployed and used.

Leverage automation in every part of a solution to accelerate and optimize all out solutions.

Architectural Reviews and Proof-of-Concepts

Work with internal resource and system implementation partners to design Datawarehouse and DataMart structures.

Identify data requirements and related KPIs, metrics, etc.; perform and document data source gap analysis.

Participate and drive proof-of-concept or prototyping of data systems and data solutions.

Collaboration and Stakeholder Management

Facilitate conceptual discussions to meet business objectives.

Define usage patterns and anti-patterns for data systems, processing, modelling, and storage technologies.

Bring a holistic brand and enterprise view into new data system design.

Technology Solutions and Client Engagement

Works within and across practices and organizations to design leading-edge technology or application solutions that result in profitable revenue growth for Unisys.

Conceptualizes, architects, designs, implements and supports integrated solutions for client engagements.

Advises, analyzes, researches, designs, installs and implements complex integrated solutions for an entire enterprise.

Interfaces extensively with the client’s senior management team (e.g., the IT Directors) on business, systems architectural, and technical issues.

Mentors and leads a team of architects.

Project Planning and Implementation

Develops the integrated technology requirements project plan.

Integrates complex solutions into new or existing client environments.

Advanced Analytical and Design Capabilities

Ensures that the best solution is provided to the customer (e.g., completes solution integrity engineering and development attributes).

Qualifications

• University degree or equivalent experience and a minimum of 10 years of experience in a broad range of data sources including SQL and NOSQL
• Data Architect experience (5+ years)
• Experience in one or more related cloud platform technology areas that interests you, for example: SQL Server, Data Lake Storage, Data Movement/Transformation e.g. Azure Data Factory/AWS Glue, Data Analytics e.g. Databricks/Synapse/BigQuery, Data Cataloguing, Data Quality, Data Lineage, Data Governance, Data Mesh/Lakehouse, Master Data Management etc.
• Some knowledge of common industry tooling covering areas such as ingestion, streaming, storage, visualisation etc.
• Experience with hands-on implementation on cloud platforms including at least one of: Microsoft Azure, Amazon Web Services, Google Cloud
• Design experience on Data Vault, Data Lake and Mart technologies in Cloud
• Experience using advanced SQL functions and query performance tuning
• Experience of Data Catalogue tools (e.g. Collibra, Informatica)
• Strong knowledge of master data management
• Knowledge of Business Objects, Tableau etc
• Knowledge and/or experience with service-oriented architecture entities and frameworks
• Knowledge of database performance/tuning/measurement, as well as user access and data manipulation
• Experience in Conceptual, Logical, and Physical Data Model design
• Strong knowledge of entity relationships
• Hands on skills in SQL, Python, AWS & Azure infrastructures, Alteryx & Tableau
• Strong knowledge of SQL, C#, SOA and web services
• Documented experience (at least 2 years) with ETL in the context of data warehouses
• Knowledge of Big Data environments (Hadoop & PhP)
• Seeing the Big Picture
• Expertise and experience to translate data related business requirements into technology solutions
• Deep expertise of various form of databases – RDBMSs, MongoDB, Cassandra, Hadoop, Spark etc. and database query languages – SQL, NoSQL
• Strong expertise in business intelligence (BI) software – Tableau, Power BI, Chartio, and related programming languages – Python