What are the responsibilities and job description for the Data Architect position at WSSC Water?
This is a non-merit employment-at-will contract position.
The Data Architect plays a critical role in designing and implementing secure, scalable data architectures that integrate operational and enterprise data from sources such as SCADA systems, IoT devices, sensors, and business platforms. This position is responsible for developing a unified data ecosystem that enables real-time data processing, advanced analytics, and data-driven insights to support optimized operations, predictive maintenance, and informed decision-making.
The Data Architect plays a critical role in designing and implementing secure, scalable data architectures that integrate operational and enterprise data from sources such as SCADA systems, IoT devices, sensors, and business platforms. This position is responsible for developing a unified data ecosystem that enables real-time data processing, advanced analytics, and data-driven insights to support optimized operations, predictive maintenance, and informed decision-making.
The role ensures the integrity, security, and governance of data by establishing and enforcing industry-compliant standards, protecting sensitive water system information while promoting accessibility and reliability across the organization. Leveraging modern cloud technologies and data platforms, the Data Architect drives the transformation of data into a strategic asset, enhancing asset management, water quality monitoring, and overall operational performance supporting the delivery of safe, reliable, and high-quality water services.
Essential Functions
- Lead the design, development, and implementation of scalable and secure data architectures that support WSSC Water’s operational systems and data needs
- Develop and maintain data models, database schemas, and data warehouses tailored to the water and wastewater industry
- Design, integrate and optimize real-time data pipelines to support the integration of operational data from various sources (e.g., SCADA, GIS, sensors, IoT devices, field data and enterprise systems)
- Design ETL (Extract, Transform, Load) processes to ensure smooth, efficient data flow between operational systems and analytics platforms
- Ensure data consistency, quality, and availability across different platforms, supporting both historical and real-time analytics
- Develop hybrid cloud architectures to leverage cloud computing platforms (e.g., AWS, Azure, GCP, OCI) while maintaining necessary on-premises solutions
- Ensure seamless integration between on-premises and cloud data environments for scalability, flexibility, and cost-effectiveness
- Lead cloud migration initiatives, ensuring that legacy systems are efficiently transitioned to modern cloud-based infrastructure
- Design robust security practices, including data encryption, access controls, and data masking protocols, to protect sensitive water and wastewater data, ensuring compliance with regulatory requirements
- Collaborate with IT security teams to establish data governance frameworks, risk mitigation strategies, and incident response plans
- Establish and enforce data governance policies and practices to ensure data accuracy, consistency, and reliability across all systems
- Develop frameworks for data lineage, metadata management, and data cataloging to improve data traceability and transparency
- Lead initiatives to improve data quality by identifying issues and implementing solutions for cleansing, standardization, and validation
- Design data architecture to support advanced analytics, machine learning, and AI workloads for predictive modeling, asset management, and operational optimization
- Ensure that data infrastructure supports real-time analytics for enhanced decision-making and monitoring of water quality, usage patterns, and infrastructure performance
- Work closely with data science teams to provide the necessary data structures and processes to enable data-driven insights
- Document data architecture designs, processes, and systems to ensure transparency, maintainability, data usage, integration procedures, and security protocols to enable team collaboration and compliance
- Conduct training and knowledge-sharing sessions for internal teams to improve understanding of data systems and best practices
Other Functions
- Partner with stakeholders across WSSC Water, including operations, engineering, regulatory compliance, and customer service, to align data architecture with business goals
- Provide technical leadership and mentorship to a team of data engineers, analysts, and other data professionals
- Lead the evaluation and selection of third-party tools, platforms, and vendors to support data architecture and integration efforts
- Continuously monitor the performance of data architecture systems and implement optimizations for speed, reliability, and cost-effectiveness
- Design systems that are highly available and resilient to ensure continuous operations in the event of system failures or disruptions
- Scale data infrastructure to accommodate growing volumes of data, supporting increased usage and future technological advancements
- Stay current with emerging technologies, industry trends, and best practices related to data architecture, cloud computing, big data, and data security
- Proactively identify opportunities for innovation and process improvements in data systems, ensuring that WSSC Water maintains a competitive edge in the water and wastewater sector
- Contribute to the long-term strategic vision for data architecture, helping to drive digital transformation across the organization
- Perform other related duties as required
Work Environment And Physical Demands
Business casual office environment
Required Knowledge, Skills, And Abilities
- Expertise in designing scalable data systems, including data modeling (conceptual, logical, and physical), data standardization, data lifecycle management, and building data lakes and warehouses to support large-scale integration and analytics
- Proficiency managing data lakes, performing analytics, and optimizing data warehousing solutions (e.g. Azure Synapse Analytics)
- Strong experience designing data pipelines, transforming large datasets, and supporting real-time analytics and machine learning or other ETL tools such as Azure Databricks, Azure Data Factory, Apache Nifi etc.
- Proficiency in SQL, Python, Scala, or Java for managing and processing data across systems, particularly in Azure Databricks
- Knowledgeable in big data technologies (e.g., Hadoop, Spark) and their integration with cloud platforms for handling large volumes of data securely and efficiently
- Experience with scalable and secure storage of large datasets (such as Azure Data Lake Storage and Azure Blob Storage)
- In-depth knowledge of data security practices, including encryption, access control, identity management, and secure data storage
- Expertise in implementing data privacy and regulatory compliance frameworks, such as GDPR, CCPA, HIPAA, and industry-specific utility standards
- Experience in managing and securing sensitive data using tools such as Azure Security Center and Azure Key Vault
- Strong understanding of data governance frameworks, ensuring data quality, integrity, and traceability through tools such as Azure Purview and/or other metadata management tools
- Knowledge of data lineage and metadata management practices to ensure data accuracy and compliance throughout the data lifecycle and knowledge of data cataloging with tools such as Alation, Collibra, Atlan or any similar product
- Familiarity with water and wastewater management systems, including SCADA, GIS, IoT sensors, and how these integrate with data architecture
- Understanding of operational challenges in water distribution, treatment, and wastewater management, and how data systems can optimize these processes
- Strong analytical skills to troubleshoot complex data systems, identify bottlenecks, and propose data-driven solutions for improved performance and security
- Ability to design and manage cloud-based data architecture
- Expertise in integrating disparate data sources (e.g., IoT, SCADA, sensors) into centralized data repositories using modern cloud tools
- Strong project management skills to oversee the design, development, and deployment of data architecture projects, ensuring deadlines and requirements are met
- Familiarity with agile methodologies for managing data-related projects and collaborating with cross-functional teams
- Proven ability to work with different application stakeholders across the organization in designing effective data flows at the onset of large enterprise initiatives
Minimum Education, Experience Requirements
- Bachelor’s degree
- 8 years experience as a Data Architect or in a similar data-related role, with a focus on designing and implementing large-scale data systems
- 3 years experience working with cloud data management platforms such as Azure Synapse Analytics and Azure Databricks
- Experience with big data technologies such as Apache Spark, Hadoop, or equivalent, and cloud data storage solutions (e.g., Azure Data Lake Storage)
- Proficiency in SQL, Python, or Scala for data processing and transformation
- Knowledge of data modeling and data warehousing concepts for designing scalable data architectures
- Knowledge of data governance principles, such as metadata management, data lineage, data cataloging, and data quality standards
- Strong analytical and troubleshooting skills, with the ability to optimize data systems and resolve technical challenges related to performance, security, and scalability
- Ability to communicate complex technical concepts to non-technical stakeholders
- Strong collaboration skills to work with cross-functional teams and lead data-related projects
OR
- High school diploma or equivalent
- 12 years experience as a Data Architect or in a similar data-related role, with a focus on designing and implementing large-scale data systems
- 3 years experience working with cloud data management platforms such as Azure Synapse Analytics and Azure Databricks
- Experience with big data technologies such as Apache Spark, Hadoop, or equivalent, and cloud data storage solutions (e.g., Azure Data Lake Storage)
- Proficiency in SQL, Python, or Scala for data processing and transformation
- Knowledge of data modeling and data warehousing concepts for designing scalable data architectures
- Knowledge of data governance principles, such as metadata management, data lineage, data cataloging, and data quality standards
- Strong analytical and troubleshooting skills, with the ability to optimize data systems and resolve technical challenges related to performance, security, and scalability
- Ability to communicate complex technical concepts to non-technical stakeholders
- Strong collaboration skills to work with cross-functional teams and lead data-related projects