Data Engineer

OUC-posted 1 day ago

Full-time • Mid Level

Hybrid • Orlando, FL

1,001-5,000 employees

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OUC - The Reliable One is presently seeking a Data Engineer to join the Transformation division. At OUC, we don’t just work – we’re building a bright future of innovation and transformation for future generations. This is a hybrid position offering two remote workdays per week. Must be onsite Tuesdays and Thursdays. We are looking for a highly skilled and innovative profession to structure, organize, and optimize scalable data pipelines, cloud architecture, and business intelligence. This role will translate complex business needs into secure, high performance data solutions. If you thrive at the intersection of data engineering, cloud technology, and advanced analytics, this is an opportunity to make a measurable impact. OUC is an industry leader and the second largest municipal utility in Florida committed to innovation, sustainability, and our community. OUC’s mission is to provide exceptional value to our customers and community by delivering sustainable and reliable services and solutions. Join a team of visionary Change Agents, Strategists, and Community Ambassadors who understand the vital role of diverse experiences in powering creativity and industry transformation. At OUC, each position contributes to the success and achievement of our goals. Click here to learn more about what we do.

Performs ETL/ELT processes, designs data models, and implements multidimensional data architectures to optimize data processing for analytics, reporting, business intelligence, and operational decision-making.
Develops and enhances scalable data pipelines, integrations, and storage solutions across on-premises and cloud environments, ensuring high-performance, reliable data accessibility.
Builds and maintains AI/ML-ready data infrastructure, enabling seamless integration of machine learning models and automated analytics workflows.
Supports feature engineering, model training, and inference to enhance predictive and prescriptive analytics capabilities.
Executes query auditing, code reviews, quality assurance (QA), and data governance to uphold best practices in security, performance, and compliance, ensuring integrity, reliability, and accessibility of data assets.
Translates business requirements into technical designs, optimized data flows, and infrastructure solutions, ensuring alignment with organizational objectives.
Collaborates with data scientists, ML engineers, analysts, and IT teams to streamline data workflows, troubleshoot performance bottlenecks, and maintain scalable architectures for structured and unstructured data.
Generates effort assessments for data engineering projects, defining Work Breakdown Structures (WBS) to scope and estimate tasks, timelines, and resource requirements.
Supports project planning by forecasting development efforts, infrastructure needs, and optimization strategies, ensuring efficiency in execution and delivery.
Gather and interpret business requirements, translating them into optimized data pipelines, models, and infrastructure solutions that support BI, analytics, and AI-driven decision- making.
Perform data modeling using foundational and modern principles, methodologies, and automation strategies to structure data for predictive analytics, reporting, and AI-driven decision-making.
Implement secure, high-performance integrations between on-premises and cloud-based storage solutions, optimizing data accessibility for BI, analytics, and operational insights.
Develop and maintain scalable ETL/ELT pipelines for efficient data extraction, transformation, and loading, ensuring integration with AI/ML workflows or Data Analytics reporting layer.
Ensure real-time and batch processing capabilities, supporting streaming, and event-driven architectures, while implementing robust data access management solutions to facilitate secure, compliant data accessibility for business intelligence (BI), analytics, and operational decision-making.
Develop and implement hybrid cloud and on-prem data storage solutions with future-proof scalability and security.
Design and optimize multidimensional data models, ensuring efficient storage and retrieval for AI-assisted data science, analytics and reporting.
Implement star and snowflake schemas, enhancing analytical performance and query optimization.
Utilize data visualization, AI-powered analytics, and business intelligence tools to structure data for strategic for decision-making and automation.
Review and audit more complex SQL queries and ETL/ELT pipelines, ensuring efficiency, compliance, and cloud and AI-readiness, adhering to best practices and established standards.
Evaluate data engineering scripts and transformation logic, ensuring integrity, scalability, and security of structured and unstructured datasets.
Conduct troubleshooting for advanced data inconsistencies, optimizing high-performance analytics pipelines across hybrid data environments, leveraging cloud tools or AI-enhanced tuning when needed.
Collaborate with data scientists, reporting analysts, programmers, business systems analysts, solution architects, and IT teams to deliver reliable data solutions.
Identify opportunities and recommend automation, AI-driven improvements, cloud efficiency options, and other process and performance improvement in the data engineering process.
Define and generate effort assessments for data engineering tasks, establishing work breakdown structures (WBS) to scope, estimate, and track project execution.
Forecast development efforts, infrastructure requirements, and reporting, Cloud, AI/ML data processing needs, ensuring efficiency and resource allocation.
Support Agile methodologies, aligning engineering workflows with business strategy and evolving project demands.
Apply data governance, AI-augmented security, privacy protocols, and compliance best practices.
Adhere to ethical guidelines and legal regulations governing the collection and use of data, including and not limiting to closed-source intelligence, open-source intelligence data, and AI- generated insights.
Maintain security and confidentiality of sensitive information and data; Perform other duties as assigned.

Bachelor’s Degree in Information Technology, Computer Science, Computer Engineering, Management Information Systems, Mathematics, Statistics, or a related field of study from an accredited college or university.
In lieu of a degree, equivalent combination of education, certifications, and experience may be substitutable on a 1:1 basis
Minimum of 3 years of experience in SQL or Python programming, ETL/ELT processes, data warehousing & cloud, data modeling and architecture, data security and governance, and visualization and reporting.
Programming languages savvy & Query Optimization expert.
Expertise in SQL, Python, and Scala, ensuring optimized query performance for structured and unstructured data processing.
Proficiency in two or more of the following languages for diverse technical implementations: JavaScript (Snowpark), DAX, Power Query (M), WDL, Power Fx, C#, Perl, VBA, R, Julia.
Strong understanding of big data frameworks and distributed computing for scalable analytics.
Proficiency in ETL/ELT tools, including Talend, Dataiku, Alteryx, Snowpipes, Azure Data Factory, SSIS.
Experience in workflow automation using Power Automate and cloud-based integration platforms.
Expertise in real-time and batch processing, supporting streaming data and event-driven architectures.
Strong knowledge of cloud-native data solutions, including Snowflake, Databricks, AWS S3, Azure Synapse, and relational databases like Oracle, MySQL.
Proficiency in VM-based deployments using Azure VMs, AWS EC2, Google Compute Engine for scalable data processing.
Familiarity with IBM Framework for structured data modeling, governance, and analytics.
Experience in data lakes, warehouse optimization, and hybrid cloud architectures for scalable analytics.
Expertise in data modeling methodologies: Inmon, Kimball, Data Vault, ensuring robust analytics solutions.
Proficiency in IBM Framework, Dataiku, Alteryx, Cognos Analytics, Power BI, and DBeaver to structure enterprise-wide data solutions.
Ability to design AI/ML-ready architectures, supporting predictive and prescriptive analytics.
Strong knowledge of role-based access control (RBAC), encryption strategies, data lineage, and compliance frameworks.
Familiarity with GDPR, CCPA, HIPAA, NIST, BCSI, and security protocols for data governance and regulatory compliance.
Ability to implement industry best practices for secure data management in cloud and VM environments.
Proficiency in Power BI, Tableau, and Cognos Analytics, enabling data-driven decision-making through interactive dashboards.
Strong critical thinking and problem-solving capabilities for optimizing insights.
Ability to translate business needs into technical solutions, ensuring structured data workflows.
Ability to effectively communicate insights to non-technical stakeholders, gather and translate business requirements into scalable data architectures.
Expertise in Work Breakdown Structures (WBS), effort estimation, and resource planning for efficient project execution.
Strong collaboration skills with data scientists, ML engineers, analysts, and IT teams.
Strong critical thinking and problem-solving capabilities.
Business acumen with a curiosity for data-driven decision-making.
Ability to rapidly learn and adapt to evolving analytics and reporting tools.
Ability to interpret and analyze data.
Ability to make arithmetic computations using whole numbers, fractions and decimals, and compute rates, ratios, and percentages
Ability to use Microsoft Office Suite (Outlook, Excel, Word, etc.) and standard office equipment (computer, telephone, fax, copier, etc.)

Master’s Degree in Data Engineering, Information Systems, Computer Science, Mathematics or Statistics, or a related field of study from an accredited college or university (preferred).
SnowPro® Advanced: Data Engineer
Databricks Certified Data Engineer
IBM Certified Data Engineer – Cognos Analytics
IBM Data Engineering Professional Certificate (Coursera)
Cloudera Certified Professional (CCP) Data Engineer
Google Cloud Professional Database Engineer
Microsoft Azure Data Engineer Associate
Snowflake SnowPro Certification
SnowPro® Associate: Platform Certification
SnowPro® Core Certification
SnowPro® Specialty: Snowpark
SnowPro® Specialty: Native Apps
SnowPro® Advanced: Architect
IBM Certified Solution Architect – Cloud Pak for Data
AWS Certified Data Analytics
AWS Certified Solutions Architect – Professional
Microsoft Certified: Azure Solutions Architect Expert
TOGAF 9 Certification
Google Data Engineering Professional Certificate
Oracle Certified Professional or MySQL Database Administrator
Coursera/Udemy Data Engineering Bootcamps
Zachman Certified Enterprise Architect

Competitive compensation
Low-cost medical, dental, and vision benefits and paid life insurance premiums with no probationary period.
OUC’s Hybrid Retirement Program includes a fully-funded cash balance account, defined contribution with employer matching along with a health reimbursement account
Generous paid vacation, holidays, and sick time
Paid parental leave
Educational Assistance Program, to include tuition reimbursement, paid memberships in professional associations, paid conference and training opportunities
Wellness incentives and free access to all on-site OUC fitness facilities
Access to family-oriented recreational areas
Paid Conference and Training Opportunities
Free downtown parking
Hybrid work schedule

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