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Data Mesh Jobs (NOW HIRING)

Nastech Global

Starburst Data Engineer

Richmond, VA · On-site

$113K - $136K/yr

Starburst Data Engineer, Starburst Presto, Data Mesh using Starburst, SQL, cloud services, and APIs. * Experience: Minimum 6 years. * Experience with Query Federation solutions-Starburst Presto ...

Tiger Analytics Inc.

Data Architect

Westwood, MA · On-site

$71.25 - $91.75/hr

Produce conceptual, logical, and physical data models aligned to business capabilities, modernization goals, and data mesh principles. * Design and implement data architecture patterns to support ...

Tiger Analytics Inc.

Data Architect

Westwood, MA · Remote

$71.25 - $91.75/hr

Produce conceptual, logical, and physical data models aligned to business capabilities, modernization goals, and data mesh principles. * Design and implement data architecture patterns to support ...

Nastech Global

Data Architect

Jersey City, NJ · On-site

$66.50 - $85.50/hr

Experience with scalable data mesh architectures on Azure * Azure Data Factory * Databricks * Strong analytical skills using software tools and reporting techniques * Familiarity with regulatory ...

Tiger Analytics Inc.

Data Architect

Westwood, MA · On-site

$71.25 - $91.75/hr

Produce conceptual, logical, and physical data models aligned to business capabilities, modernization goals, and data mesh principles. * Design and implement data architecture patterns to support ...

Tiger Analytics Inc.

Data Architect

Johnston, RI · On-site

$64.75 - $83.25/hr

Produce conceptual, logical, and physical data models aligned to business capabilities, modernization goals, and data mesh principles. * Design and implement data architecture patterns to support ...

Tiger Analytics Inc.

Data Architect

Johnston, RI · Remote

$64.75 - $83.25/hr

Produce conceptual, logical, and physical data models aligned to business capabilities, modernization goals, and data mesh principles. * Design and implement data architecture patterns to support ...

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Data Mesh information

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$165K

$243.5K

How much do data mesh jobs pay per year?

As of Sep 9, 2026, the average yearly pay for data mesh 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 are the key skills and qualifications needed to thrive as a Data Mesh architect, and why are they important?

To thrive as a Data Mesh Architect, you need expertise in data engineering, distributed systems, and data governance, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (like AWS or Azure), data pipeline tools (such as Apache Kafka or Spark), and experience implementing data governance frameworks are typically required. Strong collaboration, problem-solving, and communication skills help drive organizational change and enable effective cross-functional teamwork. These skills are crucial for successfully designing and implementing scalable, decentralized data architectures that empower business domains and ensure data quality.

How do Data Mesh teams typically collaborate with domain experts and other departments within an organization?

In a Data Mesh framework, teams work closely with domain experts and cross-functional departments to ensure data products are tailored to specific business needs. Collaboration often involves regular meetings, shared documentation, and agile practices to align data standards, quality, and access. This decentralized approach encourages ownership within domains, but also requires robust communication and governance to maintain consistency across the organization. Effective teamwork helps bridge technical and business perspectives, leading to more valuable and usable data solutions.

What is the difference between Data Mesh vs Data Engineer?

AspectData MeshData Engineer
Primary FocusDecentralized data architecture and domain-oriented data ownershipBuilding, maintaining, and optimizing data pipelines and infrastructure
Skills & CertificationsData architecture, domain knowledge, cloud platforms, data governanceSQL, ETL tools, cloud platforms, programming languages like Python or Java
Work EnvironmentCross-functional teams, collaborative data product developmentData engineering teams, cloud environments, data warehouses
Industry UsageModern data architectures, data-driven organizationsData infrastructure, analytics, machine learning projects

While Data Mesh emphasizes a decentralized approach to data architecture and domain ownership, Data Engineers focus on building and maintaining the data pipelines and infrastructure. Both roles are essential in modern data ecosystems, with Data Mesh promoting data democratization and Data Engineers ensuring data quality and accessibility.

What is a data mesh?

A data mesh is an architectural approach to managing data in large organizations by decentralizing data ownership and enabling domain teams to handle their own data products. It emphasizes data as a product, with clear responsibilities, and often involves tools like data catalogs and automation to ensure data quality and accessibility. Data engineers and architects working with distributed systems and scalable data platforms typically implement data mesh principles.

What cities are hiring for Data Mesh jobs?

Cities with the most Data Mesh job openings:

What are popular job titles for Data Mesh?

Popular job titles for Data Mesh:

Infographic showing various Data Mesh job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data-Mesh / Enterprise Architect(Only Local and Independent Candidate)

Manhattan, NY • On-site

Sidzen LLC
See more jobs at Sidzen LLCexternal

$70.25 - $90.50/hr

Other

Posted 4 days ago

Job description

Enterprise Data Architect to define target-state architecture, reusable architecture patterns and migration roadmaps for a complex financial-services data environment. The role will focus on interpreting stored-procedure landscapes, establishing clear ownership boundaries across domains and medallion layers, and designing a scalable data-product architecture. Candidate will define reusable patterns for operational applications, ingestion, market and reference data, extracts, enterprise models, master data management, sub-ledger and risk assets. The successful candidate will combine deep expertise in data mesh, data-product architecture, lakehouse platforms and financial-services data with the ability to produce practical architecture artefacts that can guide implementation. Candidate will work across business, data, platform and engineering teams to ensure that the platform enables domain ownership without owning the underlying domain data.

The Role

Responsibilities:

  • Interpret the stored-procedure landscape analysis architecturally: where a single procedure conflates responsibilities belonging to different domains or different medallion layers, define how it is split.
  • Define one reusable target pattern per MCDB feature class: operational UI / applications (app), raw ingestion from systems of record (stage), third-party market and reference data (refdata), consumer extracts (extract), enterprise model, and the cross-cutting MDM, sub-ledger and risk assets.
  • Map every inventory item to a pattern and produce the pattern-assignment matrix.
  • Compose the target-state conceptual architecture on DEAL: source-aligned data products, aggregate and consumer-aligned data products, the federated governance plane, the self-serve platform and the catalogue of catalogues — with the platform provisioning capability but never owning domain data.
  • Define the medallion mapping for each pattern
  • Specify output-port design so that contract-governed subscriptions replace point-to-point extracts, and define the change-feedback loop from consumer to producer.
  • Produce the complexity, risk and dependency assessment and sequence the roadmap against it.
  • Deliverables owned
  • Architecture pattern catalogue, one per feature class (Word; TOGAF pattern cards)
  • Pattern-assignment matrix covering every inventory item (Excel)
  • Target-state conceptual architecture (C4 and/or ArchiMate diagram + narrative)
  •  Complexity, risk and dependency assessment with sequenced roadmap (Word + diagram)

Requirements:

  • 10+ years in data architecture, 5+ at enterprise or principal level in financial services.
  • Genuine data mesh / data-product architecture delivery, not familiarity with the literature. Candidates must be able to describe a specific domain decomposition they authored, the contested boundaries within it, and how the platform-versus-domain responsibility split was enforced.
  • Deep lakehouse and medallion architecture: Databricks with Unity Catalog, Delta, Snowflake, Kafka, Airflow, Azure Data Lake Storage Gen2. Must be able to reason about equivalents on AWS (Lake Formation, Glue Data Catalog, Amazon DataZone) when comparing options for client.
  • Reference and master data architecture: vendor onboarding, identifier crosswalks across FIGI, LEI/GLEIF, CUSIP/ISIN, SEDOL and MIC, mastering and distribution to consuming domains.
  • SQL Server and T-SQL depth sufficient to reason about stored-procedure decomposition — the ownership boundaries in MCDB are inside the procedures, not the schema names.
  • TOGAF 9 or 10 certified, with demonstrable use of TOGAF to define and govern patterns; ArchiMate or C4 modelling in production use.

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