Data Architect

Unisys•Long Beach, CA

About The Position

This role involves working with business leads and systems implementation partners to define database/data warehousing requirements and data interfaces. You will conduct data model reviews, collaborate with other architects and engineering leads to integrate data security, management, and engineering excellence into solutions. The position requires consulting with internal teams and client stakeholders on proposed solutions, their development, deployment, and usage, and leveraging automation to accelerate and optimize solutions. You will design Data Warehouse and Data Mart structures, identify data requirements and KPIs, perform data source gap analysis, and participate in proof-of-concept or prototyping of data systems. This role will heavily involve stakeholder interaction and data modeling, with less focus on enterprise or infrastructure architecture. You will create documents to ensure development consistency, understand data flows, and manage the data management workstream. The role enables the build of a greenfield data warehouse on top of an existing data lake for effective analytics, facilitates conceptual discussions, defines usage patterns and anti-patterns for data systems, and brings a holistic brand and enterprise view into new data system design. You will conceptualize, architect, design, implement, and support integrated solutions for client engagements, demonstrating extensive knowledge of industry, technology, and strategy trends to drive profitable revenue growth. You will build relationships with product development organizations, advise on complex integrated solutions for an enterprise, and interface with the client's senior management. This role also includes mentoring and team leadership for other architects, developing integrated technology requirements project plans, and integrating complex solutions into client environments using advanced diagnostic, analytical, and design capabilities to ensure the best customer solution.

Requirements

University degree or equivalent experience
Minimum of 10 years of experience in a broad range of data sources including SQL and NOSQL
5+ years of Data Architect experience
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)
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

Responsibilities

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
Work with other architects and engineering leads to build data security, management and engineering excellence into all our 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
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
Participate in architectural reviews, ensuring the best patterns are in place, while early identify upstream and downstream side effects
Create documents that ensure consistency in development across the organization
Work with the key stakeholders to understand the data flows within the organization and the stakeholders needs
Manage data management workstream
Assess the logical and physical data models required to deliver this
Enable the build of a greenfield data warehouse which sits on top of their existing data lake and allows the teams to deliver effective analytics
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
Conceptualize, architect, design, implement and support integrated solutions for client engagements
Advise, analyze, research, design, install and implement complex integrated solutions for an entire enterprise
Interface extensively with the client’s senior management team on business, systems architectural, and technical issues
Provide mentoring and team leadership to other architects
Develop the integrated technology requirements project plan
Integrate complex solutions into new or existing client environments
Use advanced diagnostic analytical and design capabilities
Ensure that the best solution is provided to the customer