Senior Analytics Engineer

The Senior Analytics Engineer is responsible for designing, building, and maintaining critical data pipelines, data models, and infrastructure solutions that enable data products across project delivery, operations, and business functions. This is a hands‑on implementation role focused on delivering production‑ready data solutions. The ideal candidate has direct experience building data pipelines and analytics solutions used by business stakeholders and is comfortable working with complex, fragmented data across multiple systems. What Success Looks Like (First 6–12 Months) Deliver production‑ready ETL/ELT pipelines supporting project, financial, and operational data Translate business requirements into clean, scalable data models with minimal rework Improve performance, reliability, and usability of existing data pipelines and reporting solutions Migrate core data infrastructure from legacy systems to modern platforms, supporting the business’s shift to a data product‑first strategy Effectively collaborate with stakeholders in AEC, design, or project‑based environments Attributes To Support The NELSON Culture Go All In. Own the Outcome. We go all in—with urgency, follow‑through, and pride in the result. Be Direct. Be Respectful. Be Authentic. We keep it real—with clarity, candor, and care. Grow with Purpose. We embrace growth—through learning, coaching, and continuous improvement. Think Bold. Execute Smart. We think boldly—and pair ambition with discipline. Make Space for Everyone. We value you—and build a culture where people can thrive and do their best work. Qualifications To perform this job successfully, an individual must be able to perform each essential duty and responsibility satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Critical features of this job are described under the headings below. They may be subject to change at any time due to reasonable accommodation or other reasons. Data Architecture & Pipeline Development Design, build, and maintain production data pipelines Develop reliable ingestion processes across structured and unstructured data sources Support integrations across enterprise and design‑related platforms Optimize pipelines for performance, scalability, security, and cost efficiency Ensure data is reliable, scalable, and accessible Partner with IT, Enterprise and Practices to enable smooth data operations Semantic Layer, Database & Infrastructure Management Maintain cloud data stores that support analytics, reporting and other data products Own and optimize SQL queries, stored procedures, and scheduled jobs for data product workflows Build and maintain analytics‑ready data models and semantic layers Align data models to business logic, metrics, and data product needs Evaluate and recommend improvements to tools, data structures, and analytics approaches Ensure data quality, consistency, and usability through validation, governance, and documentation Deliver reliable datasets for business users and project teams Data Quality, Security & Governance Implement data validation, audits, and error handling Ensure compliance with data privacy, security standards, and IT policies Create documentation, metadata, data dictionaries, and best practices Requirements Translation & Solution Delivery Translate business requirements into data models and pipeline solutions Work within established architecture patterns to deliver scalable and maintainable solutions Contribute to recommendations on data structures, tools, and reporting approaches Cross‑Functional Collaboration Work with business stakeholders to understand business needs and define requirements Partner with stakeholders, analysts, and technical teams to deliver and support usable data products across functions Improve data‑driven decision making and reduce manual delivery processes Support documentation, knowledge sharing, and solution standardization Required Skills & Experience Strong proficiency in SQL and data modeling with a track record of building scalable solutions Hands‑on experience developing and maintaining ETL/ELT production pipelines Experience working with the Azure Data Platform (Data Factory, Data Lake, Databricks preferred) in production environments Proven ability integrating data across multiple systems and APIs Solid understanding of data warehousing concepts and analytics data structures Proven track record translating business needs into technical requirements and delivering actionable data products Required Industry Experience Experience working with project‑based data (financials, schedules, resource planning, or operational delivery data) Experience working in environments where data is distributed across multiple systems Preferred Experience Experience supporting data products in AEC (Architecture, Engineering, Construction), design, or real estate consulting environments OR similar project‑based industries (construction, engineering, capital projects) Experience with Deltek Vantagepoint, HubSpot, UltiPro, or similar enterprise systems Experience with BIM, CAD, or design platforms (Revit, AutoCAD, BIM 360, ACC) Experience improving data consistency across disconnected systems Experience implementing data quality frameworks to identify where data quality degrades and fix root causes, not just downstream reporting issues Experience supporting business intelligence reporting for project performance analytics, forecasting, and/or resource planning Understanding of and some hands‑on experience with the end‑to‑end business intelligence build/maintain lifecycle (data model → dataset → dashboard) using Power BI and/or Tableau Education & Experience Bachelor’s Degree in Computer Science, Data (or related field), or equivalent in appropriate education and experience 5–8+ years of experience in data engineering, BI, or analytics delivery roles Proven experience delivering production data and analytics solutions Application Expectations Candidates should be prepared to discuss: A recent example of a production data pipeline they built (tools used, approach, impact) A recent example of a complex SQL stored procedure/script/modeling project A recent example of translating facts/dimensions and business logic into actionable semantics Experience working with complex or fragmented data across multiple systems Approach to stakeholder engagement, project management and project close‑out/monitoring National Salary range: $70,000–$110,000 (compensation factors are based upon years of relevant experience, qualifications/licensure, education, and location). Additional compensation includes bonuses and benefits. Bonuses can include but are not limited to: Long Term Incentive Plan, Short Term Incentive Plan, Profit Sharing Benefits of NELSON 401(K) plan with company match Full health benefits including medical, dental, and vision Wellness program with rewards for healthy activities Pet Insurance Opportunities for career advancement Paid time off and holiday pay Paid parental leave Flexible working schedules and work from home options based on client’s needs Professional Development including discretionary support and reimbursement for registrations, certifications, and membership to a professional organization NELSON and its related affiliates are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to age, race, color, ancestry, religion, sex, sexual orientation, gender identity or expression, transgender, national origin, status as a protected veteran, disability or any other classification protected by law. #J-18808-Ljbffr