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Senior Data Solution Architect
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingDefine target data architecture and canonical domain models for analytics and agent use
Design conceptual, logical, and physical data models for BigQuery workloads
Set BigQuery standards for partitioning, clustering, and query optimization
Create source-to-target mappings, data contracts, and lineage documentation
Review SQL, schemas, and pipeline designs for scalability and cost efficiency
From the employer’s posting
Define target data architecture for cost, usage, resource, contract, finance, metadata, and operational datasets
Design conceptual, logical, and physical data models for BigQuery analytical workloads
Set BigQuery standards for partitioning, clustering, materialized views, schema conventions, and query optimization
Create source-to-target mappings, transformation rules, data contracts, lineage documentation, and business definitions
Review SQL, schemas, and pipeline designs to improve scalability, maintainability, performance, and cost efficiency
Tools in this posting
- Python
- SQL
- BigQuery
- GCP
Source — Tool mentions in context
We are seeking a hands-on Senior Data Solution Architect to design and validate a production-grade data foundation that supports analytics and AI-agent consumption. You will shape data models, integration patterns, and BigQuery standards while partnering with engineering to deliver governed, reliable datasets. Responsibilities Define target data architecture for cost, usage, resource, contract, finance, metadata, and operational datasets Design conceptual, logical, and physical data models for BigQuery analytical workloads Create source-to-target mappings, transformation rules, data contracts, lineage documentation, and business definitions Establish canonical entities, domain models, semantic datasets, and reusable dimensions for analytics and agent use cases Define data layer standards across raw, standardized, curated, and analytics-ready zones with clear ownership boundaries Design integration patterns for APIs, files, databases, event streams, and semi-structured sources Set BigQuery standards for partitioning, clustering, materialized views, schema conventions, and query optimization Review SQL, schemas, and pipeline designs to improve scalability, maintainability, performance, and cost efficiency Partner with engineering to define ingestion, transformation, enrichment, reconciliation, and data-quality patterns Establish governance standards for lineage, ownership, access control, retention, classification, freshness, and quality Coordinate architecture and code reviews and provide technical direction across the data domain Requirements Data architecture experience (3+ years) designing analytical platforms and multi-source integrations on Google Cloud Platform Technical leadership experience guiding senior engineers and aligning stakeholders on data architecture decisions Project delivery experience producing architecture artifacts, source-to-target mappings, and proof-of-concept validations Advanced SQL skills with hands-on BigQuery experience for modeling, optimization, and cost-efficient query design Strong data modeling skills across conceptual, logical, physical, dimensional, and canonical/domain models Hands-on Python skills for data services, transformations, proofs of concept, or API integrations Strong communication skills to translate requirements into clear, actionable specifications Upper-Intermediate English proficiency (B2) for daily collaboration and documentation Nice to have Google Cloud BigQuery expertise with enterprise-scale optimization and administration Python proficiency for building data tooling or integration services Data Governance experience with catalogs, lineage, and access control standards Data Model expertise for semantic layers and domain-oriented datasets Stakeholder Management experience in cross-functional, architecture-driven programs
Posting record
Report an errorActively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 1, 20262 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Oct 9, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
EPAM Systems is hiring
656 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordYour next step
Check the employer’s posting for the current role and application details.
Already applied? Track this application
Has EPAM Systems posted this job before?
Yes. We’ve followed 2 other Senior Data Solution Architect jobs there since November 2026. All 2 are still up.
About the role
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
US government figures for computer and information systems managers
- Median yearly pay, May 2025
- $175,140
- Expected change, 2025 to 2035
- 15.8% more jobsagainst 3.5% for all jobs
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
Job description
We are seeking a hands-on Senior Data Solution Architect to design and validate a production-grade data foundation that supports analytics and AI-agent consumption. You will shape data models, integration patterns, and BigQuery standards while partnering with engineering to deliver governed, reliable datasets. Responsibilities Define target data architecture for cost, usage, resource, contract, finance, metadata, and operational datasets Design conceptual, logical, and physical data models for BigQuery analytical workloads Create source-to-target mappings, transformation rules, data contracts, lineage documentation, and business definitions Establish canonical entities, domain models, semantic datasets, and reusable dimensions for analytics and agent use cases Define data layer standards across raw, standardized, curated, and analytics-ready zones with clear ownership boundaries Design integration patterns for APIs, files, databases, event streams, and semi-structured sources Set BigQuery standards for partitioning, clustering, materialized views, schema conventions, and query optimization Review SQL, schemas, and pipeline designs to improve scalability, maintainability, performance, and cost efficiency Partner with engineering to define ingestion, transformation, enrichment, reconciliation, and data-quality patterns Establish governance standards for lineage, ownership, access control, retention, classification, freshness, and quality Coordinate architecture and code reviews and provide technical direction across the data domain Requirements Data architecture experience (3+ years) designing analytical platforms and multi-source integrations on Google Cloud Platform Technical leadership experience guiding senior engineers and aligning stakeholders on data architecture decisions Project delivery experience producing architecture artifacts, source-to-target mappings, and proof-of-concept validations Advanced SQL skills with hands-on BigQuery experience for modeling, optimization, and cost-efficient query design Strong data modeling skills across conceptual, logical, physical, dimensional, and canonical/domain models Hands-on Python skills for data services, transformations, proofs of concept, or API integrations Strong communication skills to translate requirements into clear, actionable specifications Upper-Intermediate English proficiency (B2) for daily collaboration and documentation Nice to have Google Cloud BigQuery expertise with enterprise-scale optimization and administration Python proficiency for building data tooling or integration services Data Governance experience with catalogs, lineage, and access control standards Data Model expertise for semantic layers and domain-oriented datasets Stakeholder Management experience in cross-functional, architecture-driven programs
Source details
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