Title: CO - P4672 - Program Data Coordinator Location: 1111 East Main Street, Downtown, Richmond, Virginia, United States, 23219 Natural Resources and Applied Sciences Dept of Environmental Quality Hiring Range: $60,000 - $100,000 Full Time or Part Time: FULL TIME Job Description: NOTE: This is an Agency-only recruitment and is open only to current DEQ employees. Seeking to fill three vacancies: One (1) Coordinator - Stormwater and Two (2) Coordinators - VPDES/VPA. This position serves as a senior technical specialist responsible for translating water regulatory program requirements into data, business processes, and system specifications to support enterprise applications. The role applies advanced knowledge of water permitting, compliance, enforcement, and reporting frameworks to ensure regulatory programs are accurately represented in agency systems. This role is at the intersection of water program experience and technology, the position works closely with the Office of Information Services (OIS) to support system design, modernization, and integration. The incumbent ensures that permitting, compliance, enforcement, and reporting processes are accurately represented in enterprise systems, while providing the regulatory context and clarity needed for technical teams with limited program familiarity. Working closely with program staff and the Office of Information Services (OIS), the position supports system design, modernization, and integration by converting complex regulatory requirements into clear, implementable technical inputs. Assignments may support one or more programs, including the Virginia Stormwater Management Program, Virginia Pollutant Discharge Elimination System / Virginia Pollution Abatement Program, or the Virginia Wetlands Permitting Program. Please note this position follows a hybrid work schedule to include both in-office and telework. Candidates must be able to work from the assigned work location in Virginia. RESPONSIBILITIES - Translate regulatory and water program requirements into system and data specifications - Develop and document business rules, data standards, data dictionaries, and workflows - Elicit and document business requirements, user stories, and acceptance criteria - Perform process mapping and gap analysis to align program needs with system capabilities - Support user acceptance testing and validation of system functionality - Ensure data quality, integrity, and consistency across regulatory systems - Develop documentation, guidance, and training materials for technical and program staff - Collaborate with program and IT staff to support system enhancements and integration QUALIFICATIONS - Experience in water environmental regulatory programs, such as stormwater, wetlands, or wastewater permitting and/or compliance - Experience working with structured data, reporting systems, or business process documentation in support of regulatory or technical programs - Ability to translate complex regulatory requirements into clear written documentation, workflows, or technical requirements - Demonstrated analytical skills with attention to detail and data accuracy - Knowledge of data management principles, including data standards, validation, and system workflows - Knowledge of water regulatory programs, including permitting, compliance, enforcement, and reporting processes - Demonstrated ability to interpret and apply water program laws, regulations, and permit conditions in a technical or operational setting - Ability to translate application of laws, regulations, and policies into structured system requirements - Skill in business analysis, including requirements elicitation, process mapping, and gap analysis - Ability to communicate complex regulatory and technical information clearly and effectively - Effective problem-solving skills - Ability to work independently on complex assignments ABOUT US The Virginia Department of Environmental Quality (DEQ) is the primary environmental permitting agency in the Commonwealth of Virginia. It is responsible for administering laws and regulations related to air quality, water quality, water supply, renewable energy, and land protection. Through the dedication and work of over 800 employees across six regional offices and the Central Office in Richmond, DEQ issues permits, conducts monitoring and inspections, and enforces the law.

Title: Physical Science Instructor Location: Charleston United States Job Description: Salary $0.00 Annually Location Charleston County, SC Job Type FTE - Full-Time Job Number 2679 Agency Trident Technical College Residency Requirement Yes Class Code: UG70 Position Number: 61134097 Normal Work Schedule: Other Pay Grade Unclassified Opening Date 05/31/2026 EEO Statement Equal Opportunity Employer Agency Specific Application Procedures: Application for this position is limited to TTC employees occupying full-time equivalent positions. However, this position may be advertised externally at a later date. Applicants MUST complete the online SC State Jobs Employment Application. To fully evaluate qualifications, some positions may require submission of unofficial transcripts with the application. Only complete applications are considered. For assistance, contact TTC Human Resources at 843.574.6201. Application deadline is 4:00 PM, October 6, 2023. Faculty positions require the submission of related unofficial transcripts with the application and may include any required certifications. Upon hire, Official transcripts/certifications are required. Unofficial transcripts may be uploaded to the application, mailed to TTC Human Resources, PO Box 118067 Charleston, SC 29423), or faxed to 843.574.6682 or emailed in PDF format to Employment@tridenttech.edu by the deadline date and time. Employment applicants may be subject to a background check. Failure to consent to a background check will remove your application from further consideration. Background checks are conducted in compliance with the Fair Credit Reporting Act (FCRA). Trident Technical College is an equal opportunity institution and does not discriminate in the admission or employment on the basis of race, gender, color, national or ethnic origin, age, religion, disability, marital status, veteran status, sexual orientation, gender identity, or pregnancy. Veteran Preference Statement South Carolina is making our Veterans a priority for employment in state agencies and institutions. - Description - Benefits - Questions Job Responsibilities The Physical Sciences Instructor is responsible for delivering high-quality, systematically planned instruction in physical sciences courses across traditional, hybrid, and online formats. The instructor will create an inclusive and engaging learning environment that supports student success and achievement of learning outcomes while connecting course material to practical applications. Responsibilities include evaluating student performance and providing timely, meaningful feedback, as well as developing, reviewing, and revising curriculum, syllabi, and instructional materials. The instructor will also utilize a variety of teaching methods and instructional technologies to enhance student learning and adapt to evolving educational environments. The role requires maintaining regular office hours, providing academic advising, and supporting student development, recruitment, and retention efforts. In addition, the instructor will participate in curriculum planning and continuous improvement initiatives, contribute to college and community service through committees or outreach activities, pursue ongoing professional development, and perform other duties as assigned by the department head or division leadership. Minimum and Additional Requirements A master's degree in Physical Sciences is required, or a master's degree with at least 18 graduate semester hours in Physical Sciences. Preferred Qualifications The ideal candidate will demonstrate strong interpersonal, communication, and customer service skills, along with the ability to effectively engage and support diverse student populations. Experience teaching in multiple instructional formats, including online or hybrid environments, is preferred, as well as proficiency in instructional technologies and a willingness to adapt to evolving educational tools. Candidates who can teach flexible schedules and at multiple campus locations are preferred, along with those who show a commitment to continuous improvement in teaching practices, student success initiatives, and professional development. Benefits for State Employees The state of South Carolina offers eligible employees generous benefits, including health and dental insurance; retirement and savings plan options; and paid vacation and sick leave. Plus, work-life balance programs such as telecommuting and flexible work schedules are available to employees of some state agencies. Insurance Benefits Eligible employees may enroll in health insurance, which includes prescription coverage and wellness benefits. Other available insurance benefits include dental, vision, term life insurance, long term disability and flexible spending accounts for health and child care expenses. Retirement Benefits State employees are also offered retirement plan options, including defined benefit and defined contribution plans. Additionally, eligible employees may elect to participate in the South Carolina Deferred Compensation Program, which is a voluntary, supplemental retirement savings plan offering 401(k) and 457 plan options. Workplace Benefits State employees may also be eligible for other benefits, including tuition assistance; holiday, annual and sick leave; and discounts on purchases, travel and more. Note: The benefits above are available to most state employees, with the exception of those in temporary positions. Employees in temporary grant and time-limited positions may be eligible for all, some or none of these benefits as benefits are associated with each position type. For these positions, contact the hiring agency to determine what benefits may be available. 01 TTC: Please note that applicants are required to submit transcripts (Unofficial transcripts are acceptable)to be considered for this position. Applications submitted without transcripts will be considered incomplete and not accepted. Have you attached a copy of your transcripts? Unofficial transcripts may be attached, mailed to (Human Resources, PO Box 118067 Charleston, SC 29423), or faxed 843.574.6682 to the Human Resources Office. - Yes - No - Current TTC employee/Transcripts are on File 02 TTC: Are you currently employed with Trident Technical College? - Yes: Full-Time Faculty - Yes: Full-Time Staff - Yes: Part-time Adjunct Faculty - Yes: Part-time Staff - Yes: Other - No: Not currently employed with TTC 03 TTC: Applicants must complete the SC State Jobs Employment Application online. Resumes are NOT reviewed for qualifications. A resume may be attached, but not substituted for completing salary and work history or education and reference sections of the employment application. Incomplete applications will not be accepted. Is your application complete and reflects the minimum qualifications? - Yes - No 04 TTC: Where did you see this position advertised? (Check all that apply) - TTC Website - TTC Employee Referral - State Website - Post and Courier - Inside Higher Ed - Social Media - Linked In - Talent Search - Other The language used in this document does not create an employment contract between the employee and the agency. This document does not create any contractual rights or entitlements. The agency reserves the right to revise the content of this document, in whole or in part. No promises or assurances, whether written or oral, which are contrary to or inconsistent with the terms of this paragraph create any contract of employment.

Role Description We are seeking a skilled Data Engineer with strong hands-on experience in ETL development, Databricks, PySpark, Python, cloud services, and data warehousing. The primary responsibility of this role is to design, build, and maintain scalable data pipelines and backend data services that support analytics, reporting, application integrations, and enterprise data platforms. The ideal candidate should also have backend development experience and practical exposure to modern AI-enabled data solutions, including RAG, LangChain, vector databases, embeddings, and LLM-based applications. Generative AI experience is considered an added advantage and should complement the core data engineering responsibilities. Key Responsibilities - Design, develop, and maintain scalable ETL/ELT pipelines for batch and near-real-time data processing. - Build data engineering solutions using Python, SQL, PySpark, Apache Spark, Databricks, Airflow, Matillion, DBT, and related technologies. - Develop and optimize Databricks notebooks, jobs, workflows, Spark transformations, and Delta Lake-based processing pipelines. - Ingest, transform, validate, and load data from APIs, cloud storage, databases, logs, FTP/SFTP servers, files, and enterprise applications. - Work with cloud services across AWS and/or Azure, including storage, compute, serverless processing, monitoring, logging, and managed data services. - Build and maintain backend services and APIs using Python frameworks such as Flask, FastAPI, or similar technologies to expose data, trigger pipelines, and support downstream applications. - Design and support data models, curated datasets, warehouse tables, and lakehouse layers for analytics, reporting, operational dashboards, and AI-driven use cases. - Work with modern data warehouses and databases such as Snowflake, Amazon Redshift, PostgreSQL, SQL Server, MySQL, Oracle, OpenSearch, or similar platforms. - Implement data quality checks, logging, monitoring, alerting, exception handling, and pipeline failure recovery mechanisms. - Collaborate with data analysts, data scientists, backend developers, cloud engineers, and business stakeholders to deliver reliable and production-ready data solutions. - Support GenAI-enabled data use cases where required, including RAG pipelines, document ingestion, embedding generation, vector search, and LangChain-based workflows. - Assist in integrating enterprise data with LLM applications while ensuring proper metadata filtering, access controls, tenant isolation, and grounded response generation. - Participate in CI/CD, version control, deployment, and production support activities using Git, GitHub, Jenkins, Docker, CodePipeline, ECS, or similar tools. Qualifications - 6 years of experience in data engineering, ETL development, backend data services, or cloud data platforms. - Strong hands-on experience with Python, SQL, PySpark, Apache Spark, and ETL/ELT pipeline development. - Practical experience with Databricks Data Engineering, including notebooks, jobs, workflows, Spark jobs, and scalable transformation pipelines. - Experience working with cloud platforms such as AWS or Azure. - Experience with cloud services such as AWS S3, Glue, Lambda, EMR, Redshift, RDS, ECS, EC2, SQS, Azure Blob Storage, ADLS, Cosmos DB, Azure AI Search, Key Vault, Application Insights, or Log Analytics. - Strong understanding of data warehousing concepts, dimensional modeling, data marts, curated layers, and warehouse performance optimization. - Experience working with data warehouses and databases such as Snowflake, Redshift, PostgreSQL, SQL Server, MySQL, Oracle, OpenSearch, or similar systems. - Experience building backend services or APIs using Python, Flask, FastAPI, or similar backend frameworks. - Good understanding of data ingestion patterns, file formats, data validation, schema handling, metadata management, and pipeline orchestration. - Experience with workflow orchestration and transformation tools such as Airflow, Databricks Workflows, Matillion, or DBT. - Ability to troubleshoot production data issues, optimize Spark jobs, tune SQL queries, and improve pipeline performance. - Strong documentation, communication, and cross-functional collaboration skills. GenAI / AI Add-On Skills - Working knowledge of RAG architecture, including document ingestion, chunking, embeddings, retrieval, and response generation. - Experience or exposure to LangChain, prompt orchestration, LLM integration, and AI-powered search workflows. - Familiarity with vector databases or vector search platforms such as Azure AI Search, OpenSearch, ChromaDB, FAISS, Pinecone, Weaviate, Milvus, or similar tools. - Understanding of how structured, semi-structured, and unstructured data can be prepared and indexed for GenAI applications. - Exposure to LLM platforms such as OpenAI, Azure OpenAI, Claude, AWS Bedrock, or Hugging Face. - Ability to support AI applications from a data engineering perspective by preparing, securing, indexing, and retrieving enterprise data. Preferred Qualifications - Experience building production-grade data pipelines that process large volumes of records. - Experience with Delta Lake, Medallion Architecture, data lakehouse design, and Databricks performance optimization. - Experience with backend API development for data access, pipeline triggering, metadata management, or analytics integration. - Exposure to enterprise search, document intelligence, log analytics, observability, or security data platforms. - Experience with containerized deployments using Docker, AWS ECS, Kubernetes, or similar cloud-native services. - Familiarity with CI/CD pipelines, automated deployments, release documentation, and production support practices. Technical Skills - Primary Skills: Python, SQL, ETL/ELT, PySpark, Apache Spark, Databricks, Cloud Services, Data Warehousing - Data Engineering: Airflow, Matillion, DBT, Delta Lake, Data Pipelines, Data Quality, Batch Processing, Orchestration - Cloud: AWS, Azure, Snowflake - Data Platforms: Snowflake, Redshift, PostgreSQL, SQL Server, MySQL, Oracle, OpenSearch - Backend: Flask, FastAPI, REST APIs, Python Services, API Integration - GenAI Add-On: RAG, LangChain, Vector Databases, Embeddings, LLM Integration, Prompt Engineering - DevOps: Git, GitHub, Jenkins, Docker, CodePipeline, UCD, ECS Education - Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Artificial Intelligence, Machine Learning, or a related technical field.

Title: Senior Data Engineer Location: Toronto ON CA Job Description: About Flinks Flinks is the embedded finance platform that brings together connectivity, intelligence, and payments — giving businesses the infrastructure they need to build and deliver seamless financial experiences at scale. As a leader in Open Finance in Canada, we’ve grown since 2016 into one of North America’s most trusted platforms for financial data access, enrichment, and money movement. We work with innovators across many industries, including lending, fintech, banking, insurance, and wealth management. Today, our platform connects to 15,000+ financial institutions across North America and powers over 1M monthly connections. We also give our customers unprecedented visibility into 4,500+ real-time financial insights to support smarter decisioning. Companies rely on Flinks to streamline onboarding, verify income, assess credit risk, and power faster payment experiences. We’re on a mission to drive financial innovation and help businesses build financial experiences that feel effortless, connected, and customer-first. That’s where you come in. The Role We're hiring our Senior Data Engineer (Data / ML Platform) to stand up data engineering as a discipline at Flinks. You'll own the data and ML platform that turns models into reliable production services, harden the data models the business runs on and close the seam between our data scientists and the product teams. This is a high-ownership, greenfield-leaning role: much of this foundation is yours to build and own, not inherit. If you like being the person who makes data and ML production-grade - pipelines, serving, governance, reliability - and you want broad impact across a company's data, this is built for you. What You'll Do - Own and evolve the data platform - the BigQuery warehouse, dbt transformation layers, Airflow / Cloud Composer orchestration and Pub/Sub ingestion that feed every model and metric. - Build and operate the ML platform - training pipelines (Kubeflow on Vertex AI), model serving (FastAPI behind Vertex endpoints), CI/CD, containerization and typed contracts. Take operational ownership of model-serving infrastructure so reliability isn't carried by the data scientists alone. - Harden and standardize the data models the business depends on - improving schemas, fixing data-quality issues and establishing trustworthy source-of-truth feeds. - Establish data governance and observability - bring data that lives outside the warehouse under proper governance and build operational metrics for products that don't yet have them. - Standardize how data engineering is done across product lines - patterns, tooling and pipelines other teams can adopt. - Partner across data science, backend and product on the producer to consumer contract (models produced by data science, consumed/aggregated downstream, surfaced to clients). What You'll Work On You'll help build and evolve the data platform that powers Flinks' financial intelligence products, supporting everything from transaction enrichment and categorization to risk and payments decisioning. Key areas of focus include: - Building scalable data pipelines that process and transform large volumes of financial data. - Designing and maintaining reliable datasets, data models, and feature pipelines used by machine learning and product teams. - Improving data quality, observability, and operational metrics across our platform and customer-facing products. - Developing cost-efficient, high-performance data services and infrastructure that support real-time and batch workloads. - Partnering closely with Data Science, Product, and Engineering teams to enable new capabilities and accelerate product delivery. - Contributing to the evolution of our data platform architecture as we continue to scale our products, customers, and machine learning capabilities. Our stack - Python, SQL, Bash - Google Cloud Platform (GCP) - BigQuery and dbt - Airflow (Cloud Composer), Pub/Sub, and Cloud Functions - Kubeflow, Vertex AI, MLflow, and FastAPI - Docker, Terraform, and Protocol Buffers - Azure DevOps - Grafana and GCP Logging You don't need experience with every tool listed above - strong Data Engineering fundamentals and experience building production data platforms matter more than direct experience with our exact stack. SQL is the exception: it's a non-negotiable (see Key Requirements). Why This Role - Greenfield ownership — help build and evolve the data platform that powers Flinks' next generation of data and machine learning products. - High leverage impact — your work enables Data Science, Product, Engineering, and Risk teams to move faster with reliable, trusted data. - Real-world scale and complexity — work with large volumes of financial data powering products used by banks, fintechs, and financial institutions across North America. - Modern cloud-native environment — build on a modern GCP stack using contemporary data, platform, and machine learning tooling. Key Requirements - Experience: 5+ years of hands-on Data Engineering experience designing, building, and operating production data platforms, pipelines, and warehouse solutions in a cloud environment. - Data Engineering Expertise: Strong experience with ETL/ELT development, data modeling, schema design, orchestration, data quality, lineage, and warehouse optimization. Experience with BigQuery, dbt, Airflow, or equivalent modern data tooling is highly desirable. - Technical Foundation: Expert SQL and strong Python skills, with the ability to build scalable, maintainable, and well-tested data solutions that support both operational and analytical workloads. - Cloud Data Platforms: Experience working with modern cloud-native data ecosystems, including data warehouses, event-driven architectures, distributed processing, and platform observability. - Operational Excellence: Demonstrated ownership of production systems, including monitoring, reliability, performance tuning, cost optimization, incident response, and ongoing platform improvements. - Machine Learning Platform Exposure: Experience supporting machine learning workflows, feature pipelines, model-serving infrastructure, or MLOps environments is an asset, but a strong Data Engineering foundation is the primary requirement. - Collaboration: Ability to partner effectively with Data Science, Product, Engineering, and QA teams to deliver trusted, scalable, and well-governed data solutions. - Education: Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related technical field, or equivalent practical experience. - Work Authorization: Must be legally authorized to work in Canada. Compensation Range For experienced and qualified hires located in Canada, of senior (IC4) level, the compensation range is between $120,000 to $160,000 CAD annually. As part of the total rewards package, Flinks offers: - Health & Dental coverage as of Day 1 - Flexible Paid Time Off (FTO) - Remote work environment with frequent in-person gatherings and activities. - Career development, learning opportunities and growth - And more We are committed to providing accommodations for persons with disabilities. If you require accommodation, we will work with you to meet your needs. Flinks uses artificial intelligence (AI) during the recruitment process to assist in screening, assessing, or selecting applicants.