ZipRecruiter

Log In

1

Data Ethics Jobs (NOW HIRING)

eTeam

Enterprise AI-Ready Data Architect

$64.28/hr

... Data Ethics and Responsible AI Qualifications • 10+ years of experience in data architecture, process automation, implementation and large-scale data engineering, ideally in pharmaceutical • ...

Conclusive Marketing

Lead Data Scientist

Detroit, MI

Promote best practices in model governance, data ethics, and responsible AI What you need: * Minimum 5-7 years of experience in data science, analytics, or predictive modeling * Experience leading ...

OneMagnify

Lead Data Scientist

Detroit, MI · On-site

Promote best practices in model governance, data ethics, and responsible AI What you need: * Minimum 5-7 years of experience in data science, analytics, or predictive modeling * Experience leading ...

Denso

Director- Data Analytics and AI

Southfield, MI · On-site

$181K - $226K/yr

Experience establishing responsible AI, model risk management, and data ethics frameworks. Benefits Summary: * Medical, Dental, Vision, Prescription Drug plans * 401K with 4% Company Match * Vacation ...

LiveRamp

Senior Data Scientist

San Francisco, CA · On-site

A groundbreaking leader in consumer privacy, data ethics, and foundational identity, LiveRamp is setting the new standard for building a connected customer view with unmatched clarity and context ...

LiveRamp

Senior Data Scientist

San Francisco, CA

A groundbreaking leader in consumer privacy, data ethics, and foundational identity, LiveRamp is setting the new standard for building a connected customer view with unmatched clarity and context ...

LiveRamp

Senior Big Data Engineer

Little Rock, AR

$53.50 - $70.75/hr

A groundbreaking leader in consumer privacy, data ethics, and foundational identity, LiveRamp is setting the new standard for building a connected customer view with unmatched clarity and context ...

next page

Showing results 1-20

All JobsData Ethics Jobs

Data Ethics information

See salary details

$46K

$165K

$243.5K

How much do data ethics jobs pay per year?

As of Jun 27, 2026, the average yearly pay for data ethics in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What jobs will boom in 2026?

Data ethics professionals, including data ethicists and compliance officers, are expected to see increased demand as organizations focus on responsible data use and privacy regulations. Skills in data governance, legal frameworks, and ethical AI will be valuable, with roles often requiring certifications in data management or ethics. The growing emphasis on ethical AI development and data privacy will drive job growth in this field by 2026.

What does a data ethicist do?

A data ethicist analyzes ethical issues related to data collection, use, and management to ensure responsible practices. They develop guidelines, assess risks, and promote fairness and privacy in data-driven projects, often working with legal, technical, and organizational teams.

What is a Data Ethics job?

A Data Ethics job involves ensuring that data is collected, stored, and used in a responsible, fair, and transparent manner. Professionals in this role develop guidelines, assess risks, and implement ethical policies to address issues like bias, privacy, and data misuse. They collaborate with data scientists, legal teams, and policymakers to align data practices with ethical and legal standards.

What are some common challenges faced by professionals in data ethics roles?

Professionals in data ethics often encounter challenges such as balancing business objectives with privacy concerns, navigating evolving regulations, and identifying potential ethical risks in new technologies. They regularly collaborate with legal, compliance, IT, and product development teams to implement policies and ensure ethical data use throughout the organization. Additionally, the rapidly changing landscape of data-related laws and emerging technologies requires continuous learning and adaptability. Overcoming these challenges is essential for fostering responsible data practices and protecting both organizational and public interests.

How to become a data ethicist?

To become a data ethicist, individuals typically need a background in data science, ethics, philosophy, or related fields, along with knowledge of data privacy, AI, and legal standards. Gaining experience through relevant certifications, such as those in data ethics or privacy, and developing strong analytical and communication skills are also important. Many roles require a combination of technical expertise and ethical reasoning to guide responsible data use.

What are the key skills and qualifications needed to thrive in the Data Ethics position, and why are they important?

A strong background in data governance, privacy law, and ethical frameworks is critical for success in data ethics roles, often supported by degrees in data science, law, or related fields. Familiarity with data protection regulations (like GDPR or CCPA), risk assessment tools, and certifications such as CIPP or CDPSE is highly valued. Excellent communication, critical thinking, and cross-functional collaboration skills help professionals effectively advocate for ethical data practices and influence key stakeholders. These competencies ensure organizations responsibly manage data, maintain compliance, and build public trust.

Is 40 too late for data science?

Data ethics professionals and data scientists can pursue careers at any age, including 40 and beyond. Success depends on relevant skills, such as understanding data privacy, ethical frameworks, and technical tools like Python or R, rather than age. Many individuals transition into data roles later in life with appropriate training and experience.
More about Data Ethics jobs
What cities are hiring for Data Ethics jobs? Cities with the most Data Ethics job openings:
What are the most commonly searched types of Data Ethics jobs? The most popular types of Data Ethics jobs are:
What states have the most Data Ethics jobs? States with the most job openings for Data Ethics jobs include:
What job categories do people searching Data Ethics jobs look for? The top searched job categories for Data Ethics jobs are:
Data Ethics jobs near you
Infographic showing various Data Ethics job openings in the United States as of June 2026, with employment types broken down into 55% Full Time, 36% Part Time, and 9% Contract. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Enterprise AI-Ready Data Architect

Enterprise AI-Ready Data Architect

eTeam

East Hanover, NJ • On-site

Other

Posted 16 days ago

Job description

Enterprise AI-Ready Data Architect

The Enterprise AI-Ready Data Architect / Senior Data Engineer is a hybrid role with a focus on enterprise data architecture, AI integration, and hands-on data engineering. You will design and implement AI-ready, analytics-ready data products and semantic layers (including ontologies) that enable scalable enterprise analytics and integration with AI agents and GenAI use cases. You will embed governance-by-design (quality, lineage, contracts, observability) and partner closely with business and technology stakeholders—in pharmaceutical domains.

Key Responsibilities
  • Enterprise Data Architecture (AI-Ready by Design)
    • Define and deliver strategic enterprise data architectures that scale and support AI-ready outcomes.
    • Design data workflows capturing as-is and to-be states for enterprise modernization.
    • Establish architecture patterns for:
      • Semantic Context Layer
      • Data Warehouses, Data Lakehouses
      • Data Catalogs and Data Marketplaces
      • Event-driven and metadata-driven architectures
      • Distributed data management (Data Mesh, Data Fabric, Domain-Driven Design)
      • Streaming data management
  • Data Products, Semantic Products, and Master Data
    • Design data products that are AI-ready and reusable across domains and use cases.
    • Build and govern semantic models, metrics-first modeling, and ontologies (knowledge graph concepts).
    • Deliver Master Data Management (MDM) capabilities and align master/reference data with business needs.
    • Support structured and unstructured data management to enable broader AI and analytics capabilities.
  • AI Integration and GenAI Enablement
    • Enable contextual intelligence and data enrichment using:
      • Contextual retrieval, entity linking, enrichment using LLMs and embeddings
      • Vector search, RAG pipelines, and LLM-based enrichment
      • Implement graph-based approaches:
        • RDF, OWL, and SPARQL querying
        • Property graph / knowledge graph modeling for relationships and reasoning
  • Data Engineering Delivery
    • Design and implement robust ETL/ELT pipelines and orchestration frameworks.
    • Develop high-quality transformations and data modeling using:
      • Advanced SQL
      • Tools such as dbt, Airflow, Dataiku
    • Ensure production-grade engineering practices for performance, reliability, and maintainability across pipelines.
  • Governance and Standards (Embedded)
    • Implement open-source data standards across:
      • Data contracts
      • Data quality
      • Data lineage
    • Lead metadata-driven governance through metadata management, observability, and policy-aligned design.
Skills and Qualifications Core Technical Skills

• Advanced SQL proficiency • Data platforms and governance tooling experience (one or more): Snowflake, Databricks, Collibra, Salesforce • ELT/ETL and orchestration: dbt, Airflow, Dataiku • BI and reporting: Power BI • Cloud platforms: AWS, Azure, GCP • Modern architecture and data management: Data Mesh, Data Fabric, streaming, metadata-driven architecture • Graph and semantic technologies: Knowledge graphs, property graphs (Neo4J), RDF/OWL, SPARQL, graph query languages

Domain and Modeling Expertise

• Experience with data modeling techniques: Conceptual, logical, physical modeling—preferably for the pharmaceutical industry • Semantic modeling, ontology design, and reusable metric layers • MDM concepts and implementation approaches

AI and GenAI Enablement Skills

• Familiarity with GenAI technologies for enhancing analysis/reporting and data enrichment • Experience with embeddings, vector search, RAG patterns, and entity resolution/linking concepts

Nice to Have

• Experience with Palantir platform

Recommended Certifications

• CDMP (DAMA) • TOGAF • EDM Council frameworks: DCAM, CDMC, Open Knowledge Graph, Data Ethics and Responsible AI

Qualifications

• 10+ years of experience in data architecture, process automation, implementation and large-scale data engineering, ideally in pharmaceutical • Advanced technical engineering and hands-on experience in data modeling for OLAP, workflow automation, AI/ML integration • ETL pipeline design and development • Bachelor's degree in computer science, information technology, engineering, or data science • Strong problem-solving skills and attention to detail. • Excellent communication skills with the ability to work with senior stakeholders to translate business requirements to technical data requirements

Apply