Senior IT Data Solution Architect at Smithfield Foods in Smithfield, VA
he IT Senior Data Solution Architect is an expert in the technologies used to capture and process data for analytics use cases. The position that requires an individual who can design and deliver enterprise information strategies and architectures for various business analytics domains across a disparate and evolving landscape of systems, data sources and technologies. The Senior Data Architect will act as a leader in major analytics platform design/deployment/improvement efforts. The Senior Data Architect will play a major role in the redesign of Smithfield's data engineering landscape to support speed, a wide variety of internal and external data sources and accessibility/usability of data. The successful candidate will be deeply involved in the design of the entire data engineering stack - including storage, compute, orchestration, access control, source code control and CI/CD. In addition, the successful candidate work with other data architects and data engineers to develop data pipeline design patterns to streamline the data pipeline build/deploy process and reduce time-to-market. For complex data engineering needs, the successful candidate will work with data engineers and analysts to identify the relevant design patterns and incorporate them into comprehensive solutions to be built by the data engineer. The Senior Data Architect answers the question s this possible, and how can we do it? Core Responsibilities Assist in leading data platform design and deployment including the following components:
data ingestion, data storage, compute, pipeline orchestration, source code control, CI/CD, access control. Partner with data engineers and analysts to develop reusable data pipeline design patterns. Design and develop physical data models (data lakes and data warehouses) utilizing dimensional modeling concepts. Work with IT teams, business analysts, and data analytics teams to understand needs of data consumers and design solutions. Serve as a principal advisor for domain technology architecture and strategy. Create and maintain enterprise analytics data architecture documentation. Collaborate with the IT Data Governance team in defining and managing standards, guidelines, and processes. Participate in the selection of emerging technologies for data management, storage, and analytics. Present project designs and architectural roadmaps to the relevant governance committees and implementation teams. Continuous improvement of existing data architecture, delivering reusable services and cost saving opportunities in line with the policies and standards of the group. Provide mentoring and coaching for architects, engineers and analysts within the IT and Business Analytics groups. The above statements are intended to describe the general nature and level of work being performed by people assigned to this job. They are not intended to be an exhaustive list of all responsibilities, duties, and skills required of personnel so classified. May perform other duties as assigned. Qualifications To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals to perform the essential functions. Bachelor's Degree from a regionally accredited four-year college or university in Computer Science, Information Systems or a related field and 5
years of relevant professional experience, or equivalent combination of education and experience, required. Minimum of 5
years' experience in the design, deployment and management of analytics data processing systems and architectures, required. Expert knowledge of data management, data integration and data platform development techniques Expert knowledge of SQL programming, including demonstrated experience with a combination of functions, stored procedures, cursors, common table expressions, dynamic SQL, data pivoting, query optimization, correlated subqueries, windowing functions, error handling and merge operations Expert knowledge of the Python programming language, with demonstrated experience utilizing Python on the Apache Spark platform Expert level knowledge of Kimball dimensional data modeling concepts and patterns Demonstrated experience deploying and utilizing a modern data engineering stack composed of data lake, dimensional data warehouse and Apache Spark-based compute platform Deep understanding of the technologies and activities required to develop, deploy and run robust data pipelines to support the derivation of insight from data Experience with cloud-based analytics platforms on AWS and/or Microsoft Azure Experience in entity relationship modeling, metadata systems, data quality tools and techniques Ability to relate architectural decisions and recommendations to business needs Experience with deployment and use of data storage technologies such as HDFS-based data lake platforms, Azure Synapse Analytics, MS SQL Server, AWS Redshift, etc. Ability to quickly learn and adopt new technology Can work with data to identify patterns, uses judgment to form conclusions that may challenge conventional wisdom, and focuses on the crux of issues to identify high leverage intervention points and strategies Applies original and innovative thinking to produce new ideas and create innovative solutions Ability to translate complex sequences of technical activity into repeatable processes Considers the relative costs and benefits of potential actions to choose the most appropriate one; acts decisively and swiftly Ability to communicate technical concepts in plain language Attention to detail Strong verbal and written communication skills High proficiency with the Microsoft Office suite (Word, Excel, PowerPoint, Visio) Ability to work well with others in a fast-paced, dynamic environment. Ability to be respectful, approachable and team-oriented while building strong working relationships and a positive work environment. Career Benefits
Salary Range:
$100K -- $150K
Minimum Qualification
Data Science & Machine Learning, Systems Architecture & EngineeringEstimated Salary: $20 to $28 per hour based on qualifications.
data ingestion, data storage, compute, pipeline orchestration, source code control, CI/CD, access control. Partner with data engineers and analysts to develop reusable data pipeline design patterns. Design and develop physical data models (data lakes and data warehouses) utilizing dimensional modeling concepts. Work with IT teams, business analysts, and data analytics teams to understand needs of data consumers and design solutions. Serve as a principal advisor for domain technology architecture and strategy. Create and maintain enterprise analytics data architecture documentation. Collaborate with the IT Data Governance team in defining and managing standards, guidelines, and processes. Participate in the selection of emerging technologies for data management, storage, and analytics. Present project designs and architectural roadmaps to the relevant governance committees and implementation teams. Continuous improvement of existing data architecture, delivering reusable services and cost saving opportunities in line with the policies and standards of the group. Provide mentoring and coaching for architects, engineers and analysts within the IT and Business Analytics groups. The above statements are intended to describe the general nature and level of work being performed by people assigned to this job. They are not intended to be an exhaustive list of all responsibilities, duties, and skills required of personnel so classified. May perform other duties as assigned. Qualifications To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals to perform the essential functions. Bachelor's Degree from a regionally accredited four-year college or university in Computer Science, Information Systems or a related field and 5
years of relevant professional experience, or equivalent combination of education and experience, required. Minimum of 5
years' experience in the design, deployment and management of analytics data processing systems and architectures, required. Expert knowledge of data management, data integration and data platform development techniques Expert knowledge of SQL programming, including demonstrated experience with a combination of functions, stored procedures, cursors, common table expressions, dynamic SQL, data pivoting, query optimization, correlated subqueries, windowing functions, error handling and merge operations Expert knowledge of the Python programming language, with demonstrated experience utilizing Python on the Apache Spark platform Expert level knowledge of Kimball dimensional data modeling concepts and patterns Demonstrated experience deploying and utilizing a modern data engineering stack composed of data lake, dimensional data warehouse and Apache Spark-based compute platform Deep understanding of the technologies and activities required to develop, deploy and run robust data pipelines to support the derivation of insight from data Experience with cloud-based analytics platforms on AWS and/or Microsoft Azure Experience in entity relationship modeling, metadata systems, data quality tools and techniques Ability to relate architectural decisions and recommendations to business needs Experience with deployment and use of data storage technologies such as HDFS-based data lake platforms, Azure Synapse Analytics, MS SQL Server, AWS Redshift, etc. Ability to quickly learn and adopt new technology Can work with data to identify patterns, uses judgment to form conclusions that may challenge conventional wisdom, and focuses on the crux of issues to identify high leverage intervention points and strategies Applies original and innovative thinking to produce new ideas and create innovative solutions Ability to translate complex sequences of technical activity into repeatable processes Considers the relative costs and benefits of potential actions to choose the most appropriate one; acts decisively and swiftly Ability to communicate technical concepts in plain language Attention to detail Strong verbal and written communication skills High proficiency with the Microsoft Office suite (Word, Excel, PowerPoint, Visio) Ability to work well with others in a fast-paced, dynamic environment. Ability to be respectful, approachable and team-oriented while building strong working relationships and a positive work environment. Career Benefits
Salary Range:
$100K -- $150K
Minimum Qualification
Data Science & Machine Learning, Systems Architecture & EngineeringEstimated Salary: $20 to $28 per hour based on qualifications.
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