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Data Products Designer

Pay
Pay not listedSimilar roles state $122K–$190K
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Define data products with stakeholders: scope, ownership, consumers, SLAs and data contracts

  • Design logical and physical data models for lakehouse and medallion layers on Databricks and AWS

  • Re-engineer legacy data structures into reusable data products rather than copying them as-is

  • Define source-to-target mappings for Fivetran pipelines and SAP and non-SAP sources

  • Define data quality rules, business definitions and lineage expectations with engineers and governance teams

From the employer’s posting
Work with business and technical stakeholders to define data products: scope, ownership, consumers, SLAs, and data contracts.
Design logical and physical data models (conceptual, dimensional, and lakehouse/medallion layers) for data products on Databricks and AWS.
Re-engineer legacy data structures and transformation logic into well-modeled, reusable data products rather than replicating them as-is.
Define source-to-target mappings for pipelines ingested via Fivetran and from SAP and non-SAP sources.
Define data quality rules, business definitions, and lineage expectations with data engineers and governance teams.
Apply at IBM

Posting record

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Actively hiringFirst seen by us 3 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 1, 20263 days ago
Recorded sightings
4
Last seen by us
Nov 4, 2026
Employer says posted
Oct 28, 2026

We found this posting on the National Labor Exchange. These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$122K–$190K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 321 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 3

Early. Similar jobs usually come down between day 6 and day 47.

From 1,405 similar postings that came down. Coming down is not always a hire.

IBM is hiring

272 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • SQL
  • AWS
  • Databricks
  • Delta Lake
  • Fivetran
  • Kafka
  • SAP
Where the posting names them
• Strong hands-on expertise in dimensional, relational, and lakehouse data modelling, including data products/data mesh concepts and source-to-target mapping. • Strong SQL skills and experience with Databricks (Delta Lake, Unity Catalog), AWS data services, and data modelling tools such as Erwin or ER Studio. • Experience designing scalable, reliable data solutions for unstructured and real-time/near-real-time data using Kafka, Amazon EventBridge, Amazon SQS, or similar technologies.
• Work with business and technical stakeholders to define data products: scope, ownership, consumers, SLAs, and data contracts. • Design logical and physical data models (conceptual, dimensional, and lakehouse/medallion layers) for data products on Databricks and AWS. • Re-engineer legacy data structures and transformation logic into well-modeled, reusable data products rather than replicating them as-is.
• Experience in the utilities or energy industry. • Databricks and/or AWS certification, with Agile delivery experience. • Exposure to NLP, analytics, statistical, or big-data technologies.
**Preferred technical and professional experience** • Experience with Fivetran or similar ELT tools, Collibra or similar metadata/catalogue platforms, and relational-to-Databricks/Lakebase migrations. • Knowledge of SAP IS-U, SAP-native data products, SAP Business Data Cloud, and SAP BTP.
• Re-engineer legacy data structures and transformation logic into well-modeled, reusable data products rather than replicating them as-is. • Define source-to-target mappings for pipelines ingested via Fivetran and from SAP and non-SAP sources. • Assess and align with SAP-native data products so that SAP and non-SAP data are modeled consistently.
• Strong SQL skills and experience with Databricks (Delta Lake, Unity Catalog), AWS data services, and data modelling tools such as Erwin or ER Studio. • Experience designing scalable, reliable data solutions for unstructured and real-time/near-real-time data using Kafka, Amazon EventBridge, Amazon SQS, or similar technologies. • Ability to optimize modern data platforms for performance and translate business requirements into reusable, governed data products.
• Experience with Fivetran or similar ELT tools, Collibra or similar metadata/catalogue platforms, and relational-to-Databricks/Lakebase migrations. • Knowledge of SAP IS-U, SAP-native data products, SAP Business Data Cloud, and SAP BTP. • Experience in the utilities or energy industry.

Your next step

Complete your application on www.ibm.com. The employer’s form will show what is required.

Already applied? Track this application

Has IBM posted this job before?

Yes. We’ve followed 23 other Data Products Designer jobs there since November 2026. All 23 are still up.

  1. Research Triangle ParkStill up after 3 days, first seen Nov 1
  2. New YorkStill up after 3 days, first seen Nov 1
  3. DallasStill up after 3 days, first seen Nov 1
  4. HoustonStill up after 3 days, first seen Nov 1
  5. BostonStill up after 3 days, first seen Nov 1
  6. AtlantaStill up after 3 days, first seen Nov 1
  7. New YorkStill up after 3 days, first seen Nov 1
  8. ChicagoStill up after 3 days, first seen Nov 1
  9. This jobUp 3 days so far, first seen Nov 1

Large employers often post one title for several teams, so these can be separate openings.

About the role

We file this job under Analytics Engineer, by the work the posting describes.

Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.

Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.

A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

**Introduction** A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. **Your role and responsibilities** Data Products Designer to design and shape business-aligned data products as part of a large data re-engineering program. You will define data product structure, models, contracts and metadata that downstream analytics, ML and GenAI use cases will consume. Responsibilities • Work with business and technical stakeholders to define data products: scope, ownership, consumers, SLAs, and data contracts. • Design logical and physical data models (conceptual, dimensional, and lakehouse/medallion layers) for data products on Databricks and AWS. • Re-engineer legacy data structures and transformation logic into well-modeled, reusable data products rather than replicating them as-is. • Define source-to-target mappings for pipelines ingested via Fivetran and from SAP and non-SAP sources. • Assess and align with SAP-native data products so that SAP and non-SAP data are modeled consistently. • Maintain models and design artifacts in the enterprise data modeling tools • Define data quality rules, business definitions, and lineage expectations with data engineers and governance teams. • Produce design documentation and review designs with Data Engineers, Architects, and Product Owners. • Design and develop data solutions on Big Data and lakehouse technologies, including API-based data access, writing and debugging complex code where needed. • Provide technical leadership on the design of complex, high-quality and efficient data solutions, guiding team members on standards and approach. • Optimize the performance, scalability, and reliability of data products and the underlying data platform. • Collaborate with delivery teams to deliver solutions that meet business requirements and stakeholder expectations. This job can be performed from anywhere in the US **Required technical and professional expertise** • Must be able to travel 4 days per week (mandatory). • Advanced expertise in data modelling, data design, or data architecture, with demonstrated ability to design scalable data models and architectures for complex enterprise environments. • Strong hands-on expertise in dimensional, relational, and lakehouse data modelling, including data products/data mesh concepts and source-to-target mapping. • Strong SQL skills and experience with Databricks (Delta Lake, Unity Catalog), AWS data services, and data modelling tools such as Erwin or ER Studio. • Experience designing scalable, reliable data solutions for unstructured and real-time/near-real-time data using Kafka, Amazon EventBridge, Amazon SQS, or similar technologies. • Ability to optimize modern data platforms for performance and translate business requirements into reusable, governed data products. **Preferred technical and professional experience** • Experience with Fivetran or similar ELT tools, Collibra or similar metadata/catalogue platforms, and relational-to-Databricks/Lakebase migrations. • Knowledge of SAP IS-U, SAP-native data products, SAP Business Data Cloud, and SAP BTP. • Experience in the utilities or energy industry. • Databricks and/or AWS certification, with Agile delivery experience. • Exposure to NLP, analytics, statistical, or big-data technologies. IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
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Location & working pattern

Charlotte, NC

**Introduction** A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. **Your role and responsibilities**
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• Exposure to NLP, analytics, statistical, or big-data technologies. IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
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