Location: Remote from US Location Position: Analytics Engineer I ECC provides essential environmental, construction, and disaster response services, relying on its Data Science & Analytics Team for enterprise data pipelines, automation, Power BI datasets, and AI initiatives. As an Analytics Engineer, you transform data and technology into actionable insights to drive growth and improve performance. You design and maintain data infrastructure, develop predictive and AI-driven solutions, and collaborate with business units to optimize personnel selection, safety and core KPIs. In addition to technical expertise, you embody ECC’s vision and values—building trust, fostering collaboration, and encouraging innovation to support both team and stakeholder success. In this position, you will: - AI & Intelligent Systems Engineering: Design and deploy enterprise AI solutions using LLMs, RAG architecture, and intelligent agents aligned with ECC business needs. - Copilot & Agent Development: Build and maintain copilots and AI agents using Microsoft Copilot Studio and Microsoft Agents SDK, integrating workflows, guardrails, and telemetry. - Computer Vision & Detection Models: Develop, train, and deploy computer vision models for object detection, classification, and image analysis to support operational, safety, and analytical use cases. - Data Foundations for AI: Engineer and manage Azure‑based data pipelines that power AI retrieval, embeddings, and analytics workloads. - Automation & AI Integration: Develop Python‑based automation and integrations for APIs, document ingestion, embeddings, and AI pipeline orchestration. - Analytics & Decision Enablement: Enable AI‑driven insights by supporting trusted semantic models and datasets used across reporting, copilots, and executive workflows. - Cross‑Functional Collaboration: Partner with business and technical teams to define AI use cases, data requirements, and success metrics. - Governance, Quality & Observability: Ensure AI and data solutions meet standards for security, reliability, documentation, transparency, and responsible use. - Documentation & Production Support: Maintain clear technical documentation and support production AI systems during deployments and critical business cycles. Requirements - Bachelor’s degree in computer science, Information Systems, Engineering, Data Science, or a related field with at least 2 years of professional experience in data engineering, BI engineering, or analytics engineering; or a master’s degree in one of these fields with at least 1 year of professional experience. - Strong SQL includes window functions, performance tuning, and relational modeling. - Hands‑on experience with Azure (AI Search, ADF/Synapse, ADLS, Azure SQL, Key Vault, Functions, Fabric, Purview). - Hands-on experience with Computer vision models for classification, detection and segmentation using cloud services or offline models - Proven experience with LLMs, RAG architecture, embeddings, prompt engineering, and evaluation techniques in an enterprise setting. - Proficiency in Python for data engineering, AI pipelines, APIs, document processing, and automation. - Experience building copilots or intelligent agents using Copilot Studio, Microsoft Agents SDK, or comparable AI orchestration frameworks. - Experience with Git and CI/CD pipelines. - Understanding of data quality, observability, and structured documentation. ECC targeted salary range for US locations average is $75,762 to $103,840 annually. Actual salary offered may be affected by education, training, certifications, experience, skills, level of responsibility, and location. Benefits Offered for Full-Time positions: - Medical/Dental/Prescription/Vision Insurance - Life Insurance, Long Term Disability Insurance - Paid Time off and Holiday Pay - 401k with deferral matching, ESOP, Student Debt Reduction Program - Flexible Spending Accounts (FSA) - Educational Assistance, Mentorship Program, ECC University - Employee Referral Bonus Program - Company-matching charitable giving program

• Design, implement, and support end‑to‑end ELT pipelines (ingest → transform → publish) in Databricks/ADF • Implement data quality checks (DLT expectations, unit tests) with alerting and remediation runbooks • Build curated, analytics‑ready Delta tables using dimensional modeling for consumption by BI Developers • Implement CDC and deletion‑flag patterns; manage schema drift and partitioning/Z‑Ordering strategies • Operationalize jobs with monitoring, logging, alerting; participate in an on‑call rotation as needed • Partner with the Data Architect to align designs with standards for governance, security, and cost efficiency • Document pipelines, data contracts, and SLAs; continuously improve performance and reliability

Workstate is hiring a Senior Analytics Engineer! In this pivotal role, you will play a critical role in building and improving our analytical infrastructure, unlocking insights that drive decision making. You will be at the forefront of helping turn raw data into meaningful insights for business stakeholders across our client's company. Residents of Colombia or Argentina with the right to work in that country are eligible for this role. Responsibilities - Architect the Business Insights Foundation: Partners closely with data engineers to design and build transformation layers that serve as a single source of truth for all downstream partners. - Deliver Business-Facing Insights: Influence decision making by owning the end-to-end delivery of insights – from requirements to modeling to high-impact dashboards and self service tools. - Directly Collaborate with Stakeholders: Serve as the technical partner to business users, translating functional requirements into scalable, automated solutions. - Story-tell Using data: Develop artifacts that offer actionable insights to audiences of varying technical abilities, influencing strategy through data narratives. - Build for Scale: Design and implement core business metrics that automate operational reporting and enable deep dive self-serve capabilities. - Apply Engineering Rigor to Analytics: Improve existing infrastructure by applying software engineering best practices (versioning, modularity, testing) to data models.

Workstate is hiring a Senior Analytics Engineer! In this pivotal role, you will play a critical role in building and improving our analytical infrastructure, unlocking insights that drive decision making. You will be at the forefront of helping turn raw data into meaningful insights for business stakeholders across our client's company. Residents of Colombia or Argentina with the right to work in that country are eligible for this role. Responsibilities - Architect the Business Insights Foundation: Partners closely with data engineers to design and build transformation layers that serve as a single source of truth for all downstream partners. - Deliver Business-Facing Insights: Influence decision making by owning the end-to-end delivery of insights – from requirements to modeling to high-impact dashboards and self service tools. - Directly Collaborate with Stakeholders: Serve as the technical partner to business users, translating functional requirements into scalable, automated solutions. - Story-tell Using data: Develop artifacts that offer actionable insights to audiences of varying technical abilities, influencing strategy through data narratives. - Build for Scale: Design and implement core business metrics that automate operational reporting and enable deep dive self-serve capabilities. - Apply Engineering Rigor to Analytics: Improve existing infrastructure by applying software engineering best practices (versioning, modularity, testing) to data models.