• Build scalable and reliable data pipelines that collect, transform, load and curate data from internal systems • Augment data platform with data pipelines from external systems. • Ensure high data quality for pipelines you build and make them auditable • Drive data systems to be as near real-time as possible • Support design and deployment of distributed data store that will be central source of truth across the organization • Build data connections to company's internal IT systems • Develop, customize, configure self service tools that help our data consumers to extract and analyze data from our massive internal data store • Evaluate new technologies and build prototypes for continuous improvements in data engineering.

• Design, develop, and implement data pipelines, data integration, and data storage solutions • Partner closely with IT Managers, Enterprise Business Intelligence, Data Governance, and Data Science teams • Lead the design and build of scalable data pipelines and solutions (batch and/or streaming) • Analyze complex data elements and systems, data flow and develop conceptual, logical, and physical data models • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources • Collaborate in implementing components of data strategy – Master Data Management (MDM), data virtualization etc.

Role Description The Data Engineer supports Justice software implementation and support projects and may assist teams from across Neumo’s product sets as needed. They are responsible for ensuring data hygiene and building the scripts, processes, and infrastructure needed to prepare data for migration and conversion. This role oversees the full data conversion lifecycle—including sampling, transforming, loading, and iterative reprocessing to ensure clean, accurate, and ready‑to‑use data. The ideal candidate is a strong programmer with an automation mindset who can improve data quality, system reliability, and long‑term repeatability. - Develop and maintain Python and SQL scripts for data cleaning, transformation, and preparation. - Design, build, and optimize ETL pipelines and data workflows. - Execute data conversion activities: sampling, transforming, loading, and refining datasets. - Implement and document data hygiene standards and organize data environments for consistency and repeatability. - Handle sensitive and PII data responsibly and securely. - Analyze and tune SQL performance (indexes, partitioning, query plans). - Leverage AI and automation tools to streamline manual data processes. - Build and maintain infrastructure supporting scalable data pipelines. - Perform other duties as assigned. Qualifications - Proficiency in Python and SQL. - Strong understanding of ETL processes and data pipeline architecture. Requirements - Knowledge of database performance fundamentals. - Experience with PII handling and secure data practices. - Ability to improve data hygiene, documentation, and operational consistency. - Creative problem‑solver with an automation‑first mindset. Work Environment - Office setting with a moderate noise level. - The employee will work at an individual workstation, using a telephone and computer. Physical Demands - Must be able to remain seated for extended periods. - Regular use of a computer and other office machinery, such as printers and copy machines. - Occasional movement around the office. - Frequent communication via telephone. Company Description With the backing of four decades of public sector expertise and corporate capability, Neumo has successfully supported government services. Neumo was honored and recognized for four (4) consecutive years as a GovTech 100 Company representing the top 100 companies focused on making a difference in and selling to state and local government agencies across the United States. Neumo is committed to helping communities thrive and brings a wealth of experience combined with innovation. Today, Neumo offers more administrative and financial support to government officials than any other organization. And with a responsive, client-focused approach, we foster partnerships that give our customers the certainty they need to accomplish more. Neumo offers a competitive benefits and compensation package and are looking for team members who will thrive in our dynamic environment. Neumo is an Equal Opportunity Employer. Selection for a position will be made without regard to race, religion, national origin, sex, political affiliation, marital status, non-disqualifying physical handicap, and age.

• Own the end-to-end architecture for MLS and property data: streaming and batch pipelines, microservices, storage layers, and APIs • Design and evolve event-driven, Kafka-based data flows that power listing ingestion, enrichment, recommendations, and AI use cases • Drive technical design reviews, set engineering best practices, and make high-quality tradeoffs around reliability, performance, and cost • Design, build, and operate backend services (Python or Java) that expose listing, property, and recommendation data via robust APIs and microservices • Implement scalable data processing with Spark or Flink on EMR (or similar), orchestrated via Airflow and running on Kubernetes where applicable • Champion observability (metrics, tracing, logging) and operational excellence (alerting, runbooks, SLOs, on-call participation) for data and backend services • Build and maintain high-volume, schema-evolving streaming and batch pipelines that ingest and normalize MLS and third-party data • Ensure data quality, lineage, and governance are built into the platform from the start—supporting analytics, AI/ML, and customer-facing features • Collaborate with ML/AI engineers to design and scale AI agents that automate MLS feed onboarding, listing discrepancy triage, and other operational workflows • Collaborate closely with Product, Engineering, and Operations to shape the roadmap for our data platform, MLS capabilities, and AI-powered experiences • Mentor and unblock other engineers; elevate the overall level of technical decision-making on the team via pairing, reviews, and design guidance