What success looks like in this role:
Work with business leads and systems implementation partners to define database/data warehousing requirements and data interfaces
Conduct data model reviews with project team members/business subject matter experts
Working with our other architects and engineering leads to build data security, management and engineering excellence into all our solutions.
Consulting with internal teams and client stakeholders on proposed solutions and how they’ll be developed/deployed and used.
Leveraging automation in every part of a solution to accelerate and optimize all out solutions.
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
You will participate in architectural reviews, ensuring the best patterns are in place, while early identify upstream and downstream side effects
This will be heavily working with stakeholders and data modelling work with less of a focus on the enterprise or infrastructure architecture
You will create documents that ensure consistency in development across the organization
They will be working with the key stakeholders to understand the data flows within the organization and the stakeholders needs
Manage data management workstream
Assessing the logical and physical data models required to deliver this
Enabling the build of a greenfield data warehouse which sits on top of their existing data lake and allows the teams to deliver effective analytics
You will facilitate conceptual discussions to meet business objectives
You will define usage patterns and anti-patterns for data systems, processing, modelling, and storage technologies
You will bring a holistic brand and enterprise view into new data system design.
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.
Demonstrates extensive knowledge of industry, technology and strategy trends and uses this knowledge to generate profitable revenue growth for Unisys.
Builds relationships with product development organizations and is recognized by these organizations as a key product champion who adds value through exposure to client situations.
Advises, analyses, 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. Provides mentoring and team leadership to other architects.
Develops the integrated technology requirements project plan.
Integrates complex solutions into new or existing client environments.
Uses advanced diagnostic analytical and design capabilities.
Ensures that the best solution is provided to the customer (e.g., completes solution integrity engineering and development attributes.)
You will be successful in this role if you have:
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
Experience in architecting and designing the migration of data from one data source to another in which the data sources are not of same type such as Mainframe to Modern Databases such as Oracle
Design experience on Data Vault, Data Lake and Mart technologies in Cloud
Experience using advanced SQL functions and query performance tuning
Experience of design within a data science environment (AWS S3/ Jupyter notebooks)
Familiar with a variety of modelling approaches, tools and model repositories
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
Data warehousing, including business line and enterprise data warehouses, operational data stores, and business intelligence data structures
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
Has strong expertise and experience in data analytics, data visualization, machine learning and predictive modelling
Defines policies, procedures and models for data collection, storage, structure, access, manipulation, access and visualization
Defines technologies and tools used at various stages of data driven solution creation, maintenance and operation
Understands and connects business and technology aspects of data and its usages
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.
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This role may require access to export-controlled commodities and technology. Therefore, to conform to U.S. export control regulations, applicant should be eligible for any required authorizations from the U.S. Government.
Unisys is proud to be an equal opportunity employer that considers all qualified applicants without regard to age, caste, citizenship, color, disability, family medical history, family status, ethnicity, gender, gender expression, gender identity, genetic information, marital status, national origin, parental status, pregnancy, race, religion, sex, sexual orientation, transgender status, veteran status or any other category protected by law.
This commitment includes our efforts to provide for all those who seek to express interest in employment the opportunity to participate without barriers. If you are a US job seeker unable to review the job opportunities herein, or cannot otherwise complete your expression of interest, without additional assistance and would like to discuss a request for reasonable accommodation, please contact our Global Recruiting organization at [email protected] or alternatively Toll Free: 888-560-1782 (Prompt 4). US job seekers can find more information about Unisys’ EEO commitment here.
Skills Required
- University degree or equivalent experience and a minimum of 10 years working with diverse data sources (SQL and NoSQL)
- Data Architect experience (5+ years)
- Hands-on implementation experience on at least one cloud platform: Microsoft Azure, AWS, or Google Cloud
- Design experience with Data Vault, Data Lake and Data Mart technologies in cloud environments
- Experience designing and delivering a data warehouse / DataMart on top of a data lake
- Documented ETL experience in the context of data warehouses (at least 2 years)
- Advanced SQL skills, query performance tuning and strong knowledge of RDBMS concepts
- Hands-on skills in Python for data tasks and experience with Jupyter notebooks/AWS S3 in data science contexts
- Experience with data movement/transformation tools (e.g., Azure Data Factory, AWS Glue)
- Familiarity with Databricks, Synapse or BigQuery and big data processing (Spark, Hadoop)
- Experience with data cataloguing, data lineage, data quality and data governance concepts and tools
- Knowledge of master data management (MDM) practices and tools
- Familiarity with BI and visualization tools (Tableau, Power BI, Business Objects, Chartio) and analytics workflows
- Experience with NoSQL databases and large-scale data stores (MongoDB, Cassandra)
- Experience architecting migrations between disparate data sources (e.g., mainframe to modern DBs like Oracle)
- Experience defining conceptual, logical and physical data models and strong entity-relationship modelling skills
- Knowledge of service-oriented architecture (SOA), C#, web services and integration patterns
- Familiarity with Alteryx for data preparation and automation
- Familiarity with Collibra or Informatica data catalogue tools
- Experience with data mesh, lakehouse patterns and modern data platform design
Unisys Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Unisys and has not been reviewed or approved by Unisys.
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Fair & Transparent Compensation — Fair & Transparent Compensation: Compensation terms at hire are often presented clearly and upfront, creating a straightforward “take it or leave it” expectation. Pay outcomes are also described as variable by role and geography, with some pockets viewed as satisfactory or above average.
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Retirement Support — Retirement Support: A 401(k) plan with an employer match is commonly described as part of the core package. The match is often characterized as a meaningful component of total rewards relative to other benefits.
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Healthcare Strength — Healthcare Strength: Core medical, dental, and vision coverage is described as available and broadly in line with a large IT-services employer. The underlying carrier network is sometimes viewed as solid even when cost concerns exist.
Unisys Insights
What We Do
Unisys is a global information technology company that builds high-performance, security-centric solutions for the most demanding businesses and governments on Earth. Unisys offerings include security software and services; digital transformation and workplace services; industry applications and services; and innovative software operating environments for high-intensity enterprise computing. We build better outcomes securely for our clients across the Government, Financial Services and Commercial








