Southern New Hampshire University
Data Engineer
Southern New Hampshire University, Hooksett, New Hampshire, us, 03106
Southern New Hampshire University is a team of innovators. World changers. Individuals who believe in progress with purpose. Since 1932, our people-centered strategy has defined us - and helped us grow a team that now serves over 180,000 learners worldwide.
Our mission to transform lives is made possible by talented people who bring diverse industry experience, backgrounds and skills to the university. And today, we're ready to expand our reach. All we need is you.
Make an impact - from near or far
At SNHU, you'll have the option to work remotely in the following states: Alabama, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Mississippi, Missouri, Nebraska, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, West Virginia, Wisconsin and Wyoming.
We ask that our remote employees have access to a reliable internet connection and a dedicated, properly equipped workspace that is free of distractions. Employees must reside in, and work from, one of the above approved states.
The opportunity
Job Description
The Data Services team ensures business-relevant data is curated, accurate, accessible, and convenient for use by the business to inform data-driven our decisions and projects. The Data Engineer reports to the Data Engineering Manager, and develops, and manages the data service solutions. You will work with large volumes of data, building and maintaining the curated data, metadata, data extractions, loads, transformations, and aggregations used to support our needs. These deliverables include (but are not limited to) data pipelines, warehouses, integrations, marts, stores, lakes, virtualizations, models, and associated database objects. This role can be 100% remote in our approved working states. #LI-Remote
What you'll do:
•Analyze requirements, data sources, and performance considerations to design efficient data pipelines, storage systems, and databases.
•Ensure adherence to data governance, security, data quality, and compliance standards. •Implement data validation, data cleansing, and data profiling techniques to maintain data accuracy, consistency, and integrity.
•Collaborate with data governance teams to ensure compliance with relevant regulations and policies.
•Comprehend data requirements, provide technical expertise communicating updates and resolutions to customers and other partners to understand and address our data needs.
•Seek opportunities for professional development, attend conferences, participate in training programs, and explore solutions to enhance data engineering practices.
•Manage scalable data pipelines that extract data from several sources, transform it into a usable format, and load it into data storage systems.
•Build relational databases, data warehouses, and data lakes to ensure efficient storage and organization of structured and unstructured data.
•Use cloud-based ETL (Extract, Transform, Load) tools to ensure efficient and reliable data movement.
•Employ techniques like query optimization, indexing strategies, caching mechanisms, and parallel processing to enhance data processing speed and efficiency.
•Monitor system performance, identify bottlenecks, and implement optimizations.
•Develop algorithms and processes to clean, transform, and process data.
•Perform data normalization, aggregation, and enrichment to make it suitable for analysis.
•Implement data quality checks and validation procedures to ensure data accuracy, consistency, and completeness.
•Implement security measures to protect sensitive data and work with data protection officers to follow relevant data privacy regulations.
•Collaborate with teams, including data scientists, data analysts, software engineers, and team members.
•Monitor data pipelines, data warehouses, and related systems to resolve issues.
•Perform regular maintenance tasks, handle data backups, and provide support during incidents or outages.
•Define the data schema, improve data storage and retrieval, and ensure data integrity and security.
•Contribute to a team manage the development of mission-critical data service solutions.
•Develop, test, and improve ETL data transformations to load data from multiple operational systems to the data services environment for supporting core multi-dimensional analysis.
•Resolve business-critical issues promptly.
•Attendance, punctuality, and reliability are essential functions of this role.
•Other responsibilities as assigned.
We would like to see:
•Five years of information technology practical experience in a quantitative, data-driven business environment working with data directly.
•Degree(s): Bachelor's degree in quantitative or analytical field such as information technology, business, mathematics, engineering, analytics, or sciences. 7+ years of experience in lieu of degree acceptable.
•Technical skills with data engineering principles, and hands-on experience in data-related projects.
•Knowledge of relational database architecture, data warehousing, data manipulation, combining/aggregating data, and data extraction from multiple different data sources.
•Understanding of data integration concepts, ETL processes, data modeling, and data warehousing principles.
•Efficient in SQL programming for SQL Server and Oracle with the ability to write complex queries and scripts.
•Experience with Visual Studio and Azure Data Factory.
•Experience with Scrum, Kanban, and Agile methodologies.
•Experience in defect tracking, release management, change management, and version control.
•Solid knowledge and practice of the Software Development Lifecycle (SDLC) deployment scenarios thru DEV/TEST/STAGE/PROD stacks following industry best practices.
•Experience developing data solutions such as data warehouses, data marts, tabular models, and reports.
•Familiarity with reporting tools such as Power BI.
•Experience with Azure DevOps.
•Technical documentation skills.
•Understanding of data engineering concepts, methodologies, and best practices.
•Knowledge of data pipelines, data integration, data warehousing, and data processing techniques.
•Experience in logging, error handling, and event handling within ETL processing.
•Proficiency in developing, and optimizing data pipelines, data warehouses, and data lakes.
•Proficiency in deploying and managing data services on cloud infrastructure.
•Experience in data warehousing concepts, including dimensional modeling, data schema design, and optimization techniques.
•Understanding and solid experience in database design, performance tuning, and indexing strategies.
•Experience implementing data quality checks, data profiling, and data governance practices.
•Familiarity with data cataloging, metadata management, and data lineage.
•Strong analytical and problem-solving abilities to solve complex data engineering challenges.
•Ability to resolve performance bottlenecks and improve data processing workflows.
Would like to see:
•Knowledge of C# and PERL programming.
•Knowledge of R and Python programming languages.
•Knowledge of data mesh, data fabric, and data virtualization technologies.
•At least one year of higher education industry/sector experience.
•Knowledge of Team Foundation Server and Git source control tools.
•Experience with Redgate tools.
We believe real innovation comes from inclusion - where different experiences, perspectives and talents are celebrated. So if you're wondering whether SNHU is right for you, take the leap and apply. You might be just the person we're looking for.
Compensation
The annual pay range for this position is $80,651.00 - $129,068.00. Actual offer will be based on skills, qualifications, experience and internal equity, in addition to relevant business considerations. We expect this position to be hired in the following target hiring range $89,121.00 - $120,575.00.
Exceptional benefits (because you're exceptional)
You're the whole package. Your benefits should be, too. As a full-time employee at SNHU, you'll get:
High-quality, low-deductible medical insuranceLow to no-cost dental and vision plans5 weeks of paid time off (plus almost a dozen paid holidays)Employer-funded retirementFree tuition programParental leaveMental health and wellbeing resources
Our mission to transform lives is made possible by talented people who bring diverse industry experience, backgrounds and skills to the university. And today, we're ready to expand our reach. All we need is you.
Make an impact - from near or far
At SNHU, you'll have the option to work remotely in the following states: Alabama, Arizona, Arkansas, Delaware, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Mississippi, Missouri, Nebraska, New Hampshire, New Mexico, North Carolina, North Dakota, Ohio, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, West Virginia, Wisconsin and Wyoming.
We ask that our remote employees have access to a reliable internet connection and a dedicated, properly equipped workspace that is free of distractions. Employees must reside in, and work from, one of the above approved states.
The opportunity
Job Description
The Data Services team ensures business-relevant data is curated, accurate, accessible, and convenient for use by the business to inform data-driven our decisions and projects. The Data Engineer reports to the Data Engineering Manager, and develops, and manages the data service solutions. You will work with large volumes of data, building and maintaining the curated data, metadata, data extractions, loads, transformations, and aggregations used to support our needs. These deliverables include (but are not limited to) data pipelines, warehouses, integrations, marts, stores, lakes, virtualizations, models, and associated database objects. This role can be 100% remote in our approved working states. #LI-Remote
What you'll do:
•Analyze requirements, data sources, and performance considerations to design efficient data pipelines, storage systems, and databases.
•Ensure adherence to data governance, security, data quality, and compliance standards. •Implement data validation, data cleansing, and data profiling techniques to maintain data accuracy, consistency, and integrity.
•Collaborate with data governance teams to ensure compliance with relevant regulations and policies.
•Comprehend data requirements, provide technical expertise communicating updates and resolutions to customers and other partners to understand and address our data needs.
•Seek opportunities for professional development, attend conferences, participate in training programs, and explore solutions to enhance data engineering practices.
•Manage scalable data pipelines that extract data from several sources, transform it into a usable format, and load it into data storage systems.
•Build relational databases, data warehouses, and data lakes to ensure efficient storage and organization of structured and unstructured data.
•Use cloud-based ETL (Extract, Transform, Load) tools to ensure efficient and reliable data movement.
•Employ techniques like query optimization, indexing strategies, caching mechanisms, and parallel processing to enhance data processing speed and efficiency.
•Monitor system performance, identify bottlenecks, and implement optimizations.
•Develop algorithms and processes to clean, transform, and process data.
•Perform data normalization, aggregation, and enrichment to make it suitable for analysis.
•Implement data quality checks and validation procedures to ensure data accuracy, consistency, and completeness.
•Implement security measures to protect sensitive data and work with data protection officers to follow relevant data privacy regulations.
•Collaborate with teams, including data scientists, data analysts, software engineers, and team members.
•Monitor data pipelines, data warehouses, and related systems to resolve issues.
•Perform regular maintenance tasks, handle data backups, and provide support during incidents or outages.
•Define the data schema, improve data storage and retrieval, and ensure data integrity and security.
•Contribute to a team manage the development of mission-critical data service solutions.
•Develop, test, and improve ETL data transformations to load data from multiple operational systems to the data services environment for supporting core multi-dimensional analysis.
•Resolve business-critical issues promptly.
•Attendance, punctuality, and reliability are essential functions of this role.
•Other responsibilities as assigned.
We would like to see:
•Five years of information technology practical experience in a quantitative, data-driven business environment working with data directly.
•Degree(s): Bachelor's degree in quantitative or analytical field such as information technology, business, mathematics, engineering, analytics, or sciences. 7+ years of experience in lieu of degree acceptable.
•Technical skills with data engineering principles, and hands-on experience in data-related projects.
•Knowledge of relational database architecture, data warehousing, data manipulation, combining/aggregating data, and data extraction from multiple different data sources.
•Understanding of data integration concepts, ETL processes, data modeling, and data warehousing principles.
•Efficient in SQL programming for SQL Server and Oracle with the ability to write complex queries and scripts.
•Experience with Visual Studio and Azure Data Factory.
•Experience with Scrum, Kanban, and Agile methodologies.
•Experience in defect tracking, release management, change management, and version control.
•Solid knowledge and practice of the Software Development Lifecycle (SDLC) deployment scenarios thru DEV/TEST/STAGE/PROD stacks following industry best practices.
•Experience developing data solutions such as data warehouses, data marts, tabular models, and reports.
•Familiarity with reporting tools such as Power BI.
•Experience with Azure DevOps.
•Technical documentation skills.
•Understanding of data engineering concepts, methodologies, and best practices.
•Knowledge of data pipelines, data integration, data warehousing, and data processing techniques.
•Experience in logging, error handling, and event handling within ETL processing.
•Proficiency in developing, and optimizing data pipelines, data warehouses, and data lakes.
•Proficiency in deploying and managing data services on cloud infrastructure.
•Experience in data warehousing concepts, including dimensional modeling, data schema design, and optimization techniques.
•Understanding and solid experience in database design, performance tuning, and indexing strategies.
•Experience implementing data quality checks, data profiling, and data governance practices.
•Familiarity with data cataloging, metadata management, and data lineage.
•Strong analytical and problem-solving abilities to solve complex data engineering challenges.
•Ability to resolve performance bottlenecks and improve data processing workflows.
Would like to see:
•Knowledge of C# and PERL programming.
•Knowledge of R and Python programming languages.
•Knowledge of data mesh, data fabric, and data virtualization technologies.
•At least one year of higher education industry/sector experience.
•Knowledge of Team Foundation Server and Git source control tools.
•Experience with Redgate tools.
We believe real innovation comes from inclusion - where different experiences, perspectives and talents are celebrated. So if you're wondering whether SNHU is right for you, take the leap and apply. You might be just the person we're looking for.
Compensation
The annual pay range for this position is $80,651.00 - $129,068.00. Actual offer will be based on skills, qualifications, experience and internal equity, in addition to relevant business considerations. We expect this position to be hired in the following target hiring range $89,121.00 - $120,575.00.
Exceptional benefits (because you're exceptional)
You're the whole package. Your benefits should be, too. As a full-time employee at SNHU, you'll get:
High-quality, low-deductible medical insuranceLow to no-cost dental and vision plans5 weeks of paid time off (plus almost a dozen paid holidays)Employer-funded retirementFree tuition programParental leaveMental health and wellbeing resources