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Semantic Jobs in Massachusetts (NOW HIRING)

The Mission AtScale is the semantic layer for modern data and AI. We bridge the gap between complex cloud data platforms like Snowflake, Databricks, and Google BigQuery, and the business users and AI ...

Senior Analyst

Boston, MA · On-site +1

$95K - $126K/yr

Lead data analysis and semantic modeling for the certified data products (Rebates, Sales-to-GMR, Inventory) * Build and rationalize Power BI dashboards and semantic models * Partner with Finance and ...

BI Developer II

Boston, MA · On-site

$77 - $132/hr

The BI Developer II role drives business insights at BBC by delivering dashboards, reports, and semantic models on the Power BI platform. This role combines business intelligence development with a ...

BI Developer II

Boston, MA · On-site

$77K - $132K/yr

The BI Developer II role drives business insights at BBC by delivering dashboards, reports, and semantic models on the Power BI platform. This role combines business intelligence development with a ...

BI Developer II

Boston, MA · On-site

$77K - $132K/yr

The BI Developer II role drives business insights at BBC by delivering dashboards, reports, and semantic models on the Power BI platform. This role combines business intelligence development with a ...

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Semantic information

What is a semantic job?

A Semantic job typically involves working with meaning and context in language, data, or technology. It may include roles in natural language processing (NLP), knowledge representation, search engine optimization (SEO), or semantic web technologies. Professionals in this field develop algorithms, ontologies, and models to improve understanding and classification of information. These jobs are common in AI, data science, and digital marketing industries.

What are the key challenges faced by semantic engineers when implementing knowledge graphs in large organizations?

Semantic Engineers often encounter challenges related to integrating disparate data sources, ensuring data quality, and aligning ontologies across departments. In large organizations, there can be legacy systems and inconsistent data formats, making it difficult to create a unified semantic model. Additionally, Semantic Engineers must collaborate closely with data architects, subject matter experts, and software developers to ensure the knowledge graph accurately reflects the organization's information needs and remains scalable as requirements evolve.

What are the key skills and qualifications needed to thrive as a semantic analyst, and why are they important?

To thrive as a Semantic Analyst, you need expertise in linguistics, natural language processing (NLP), data analysis, and a relevant degree such as linguistics, computer science, or information science. Familiarity with tools like Python, NLP libraries (e.g., NLTK, spaCy), and semantic annotation systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex language data and collaborate with technical teams. These competencies are vital to accurately extract, structure, and apply meaning from language data, driving insights and solutions in various industries.

What is the difference between Semantic vs Data Analyst?

AspectSemanticData Analyst
Required CredentialsBackground in linguistics, computer science, or related fields; knowledge of semantic web technologiesDegree in statistics, mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentResearch-focused, often in tech or AI companies, working on language understandingBusiness or research settings, analyzing data to inform decisions
Industry UsageUsed in AI, NLP, and semantic web projectsUsed across finance, marketing, healthcare, and other sectors
Common Search/ComparisonSemantic vs Data Analyst

Semantic professionals focus on understanding and structuring meaning in language and data, often working with AI and NLP technologies. Data Analysts interpret data sets to generate insights for business decisions. While both roles involve data, Semantic roles emphasize language and knowledge representation, whereas Data Analysts focus on statistical analysis and reporting.

What are the most commonly searched types of Semantic jobs in Massachusetts?

The most popular types of Semantic jobs in Massachusetts are:

What are popular job titles related to Semantic jobs in Massachusetts?

For Semantic jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Semantic jobs in Massachusetts look for?

The top searched job categories for Semantic jobs in Massachusetts are:

Infographic showing various Semantic job openings in Massachusetts as of August 2026, with employment types broken down into 84% Full Time, 10% Part Time, 1% Temporary, and 5% Contract. Highlights an 71% Physical, 6% Hybrid, and 23% Remote job distribution.

Principal Software Engineer, Semantic Data Services

eNett

Boston, MA

$146K - $196K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago


Job description

Principal Software Engineer, Semantic Data Services

About the Role

WEX is reimagining its enterprise data platform with an ambitious goal: make our data understandable not only to people and applications, but also to AI models and autonomous agents.

We are looking for a Principal Software Engineer to help build the next generation of our Data-as-a-Service (DaaS) platform and the semantic foundation that connects enterprise data with its business meaning.

In this role, you will help define and build trusted semantic objects for our major business domains-such as customers, accounts, merchants, transactions, vehicles, payments, claims, and risk signals. These objects will bring together data, relationships, business definitions, derived attributes, policies, lineage, and context into reusable assets that can power analytics, data products, decisioning, and AI experiences.

You will operate as a senior technical leader and hands-on engineer, partnering with engineers, architects, Product, AI, Analytics, Risk, Finance, and business teams across WEX to solve complex data and distributed systems problems.

The space is evolving quickly. We are not looking for someone who has already built an exact version of this platform. We are looking for an engineer with deep data and platform expertise, strong technical judgment, and the ability to help invent what the next generation of enterprise data platforms should become in an AI-native world.

How you'll make an impact
  • Define and influence the architecture and technical direction for WEX's Semantic Data Lake and next generation of Data as a Service.

  • Design and build semantic business objects that bring together enterprise data, business context, relationships, metrics, derived attributes, rules, lineage, quality, and governance.

  • Develop scalable patterns and frameworks for creating semantic objects across multiple lines of business while maintaining consistent enterprise standards.

  • Build core platform capabilities across semantic modeling, ontology, metadata, knowledge graphs, data quality, lineage, data contracts, and governance.

  • Work deeply with business and product teams to translate complex business concepts into durable technical models and reusable platform capabilities.

  • Help capture business context that may exist across databases, applications, workflows, documents, policies, and institutional knowledge.

  • Enable AI and agentic applications to discover, understand, reason over, and safely act on trusted enterprise data.

  • Design reusable APIs, services, frameworks, and developer experiences that allow teams to build data products and AI experiences faster.

  • Solve complex distributed systems, data processing, scalability, reliability, and performance challenges.

  • Establish engineering patterns and architectural standards and influence adoption across teams without relying on direct authority.

  • Mentor engineers and provide technical guidance on complex architecture and implementation decisions.

  • Remain hands-on with architecture, design, prototyping, code, and critical platform components.

Experience you'll bring
  • 10+ years of experience in software engineering, data engineering, distributed systems, data platforms, or related technology areas, with demonstrated experience operating at Staff, Principal, or equivalent technical scope.

  • Deep software engineering and distributed systems expertise, with experience designing and building large-scale production platforms.

  • Deep understanding of modern data architecture, including large-scale data processing, streaming, lakehouse architectures, data products, and distributed systems.

  • Deep understanding of semantic data technologies and industry direction is essential. Direct experience building a semantic data layer is strongly recommended.

  • Experience with semantic modeling, ontology, metadata platforms, knowledge graphs, data catalogs, enterprise data modeling, or closely related technologies.

  • Demonstrated ability to translate complex business concepts into scalable technical abstractions and reusable platform capabilities.

  • Strong understanding of data quality, governance, lineage, security, privacy, and operational reliability.

  • Experience building platforms or capabilities adopted by multiple engineering teams, business domains, or product organizations.

  • Strong architectural judgment and the ability to reason through complex tradeoffs while moving comfortably between architecture and detailed implementation.

  • Demonstrated ability to influence technical direction and drive alignment across teams and organizational boundaries.

  • Strong communication skills with the ability to explain complex technical concepts to engineers, product teams, business partners, and senior leaders.

Preferred experience
  • Experience building platforms that support AI/ML, generative AI, RAG, or agentic applications.

  • Experience with knowledge representation, semantic search, context engineering, graph technologies, or AI-ready enterprise data.

  • Experience modernizing large enterprise data ecosystems with multiple business domains and legacy systems.

  • Experience with technologies such as Spark, Flink, Kafka, Iceberg, Snowflake, Databricks, cloud-native data services, graph databases, or equivalent large-scale data technologies.

  • Experience defining reusable frameworks, APIs, standards, or platform capabilities that have been broadly adopted beyond an individual team.

The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the "About Us" section.Pay Range: $200,600.00 - $250,400.00