Salesforce Data Architect

XAXIS Solutions Inc.; Chicago (IL); On-site; USD 150,000 - 210,000; Full time

Job summary

XAXIS Solutions Inc. seeks an senior Data Architect to own the enterprise data model across the Salesforce estate, optimize LDV design, and define partitioning and retention strategies to sustain performance at scale.

You will design canonical data models, map to master data definitions, and architect data integration patterns with ERP, MDM and data-platform ecosystems, including Data Cloud (Data 360). Collaborating with presales and consultants, you will establish data governance, quality KPIs

Qualifications

• 10–15 years overall with 6+ years on Salesforce and 3+ years in data architecture / Data Cloud.
• Strong Salesforce data modeling, LDV optimization, and sharing/visibility implications on the data layer.
• Hands-on Data Cloud (Data 360) — DLO/DMO, Identity Resolution, Calculated Insights, Segmentation, Activations.
• Proven large-scale data migration experience with cleansing, dedup and reconciliation frameworks.
• Strong SQL and data-integration skills (API-led, ETL/ELT, middleware); familiarity with data platforms (Snowflake / BigQuery / Redshift) is a plus.
• Understanding of MDM, data governance, and data-quality tooling and practices.

Responsibilities

• Own the enterprise data model across the Salesforce estate — objects, relationships, LDV (large data volume) design, indexing and skinny tables.
• Design canonical data models and mapping to enterprise / master-data definitions for consistency across systems.
• Define data-partitioning, archival and retention strategies to sustain performance at scale.
• Define end-to-end data migration strategy from legacy CRMs / ERPs (including cleansing, dedup, reconciliation and cutover).
• Architect data integration and synchronization patterns (API-led, ETL/ELT, batch and streaming) with ERP, MDM and data-platform ecosystems.
• Ensure reliable handling of high-volume, high-velocity data with data lineage and traceability.
• Establish data governance — ownership, stewardship, quality rules, MDM alignment and metadata management.
• Define data-quality KPIs (completeness, accuracy, duplication) and remediation frameworks.
• Ensure data privacy and compliance (GDPR / CCPA), data masking, encryption and role-based access to sensitive data.
• Support presales, data-strategy assessments, estimation and solution defence for data-centric pursuits.
• Build reusable data-migration frameworks and accelerators; mentor data engineers and consultants.

Skills

Salesforce data modeling

LDV optimization

Data Cloud (Data 360)

SQL

Data governance

Data integration

MDM awareness

Big data platforms

Data quality

Tools

Snowflake

BigQuery

Redshift

Job description

KEY RESPONSIBILITIES

• Own the enterprise data model across the Salesforce estate — objects, relationships, LDV (large data volume) design, indexing and skinny tables.
• Design canonical data models and mapping to enterprise / master-data definitions for consistency across systems.
• Define data-partitioning, archival and retention strategies to sustain performance at scale.

Data Migration & Integration

• Define end-to-end data migration strategy from legacy CRMs / ERPs (including cleansing, dedup, reconciliation and cutover).
• Architect data integration and synchronization patterns (API-led, ETL/ELT, batch and streaming) with ERP, MDM and data-platform ecosystems.
• Ensure reliable handling of high-volume, high-velocity data with data lineage and traceability.

Data Governance, Quality & Security

• Establish data governance — ownership, stewardship, quality rules, MDM alignment and metadata management.
• Define data-quality KPIs (completeness, accuracy, duplication) and remediation frameworks.
• Ensure data privacy and compliance (GDPR / CCPA), data masking, encryption and role-based access to sensitive data.

Advisory & Practice Contribution

• Support presales, data-strategy assessments, estimation and solution defence for data-centric pursuits.
• Build reusable data-migration frameworks and accelerators; mentor data engineers and consultants.

REQUIRED SKILLS & EXPERIENCE

• 10–15 years overall with 6+ years on Salesforce and 3+ years in data architecture / Data Cloud.
• Strong Salesforce data modeling, LDV optimization, and sharing/visibility implications on the data layer.
• Hands-on Data Cloud (Data 360) — DLO/DMO, Identity Resolution, Calculated Insights, Segmentation, Activations.
• Proven large-scale data migration experience with cleansing, dedup and reconciliation frameworks.
• Strong SQL and data-integration skills (API-led, ETL/ELT, middleware); familiarity with data platforms (Snowflake / BigQuery / Redshift) is a plus.
• Understanding of MDM, data governance, and data-quality tooling and practices.

CERTIFICATIONS (Nice to have)

KEY COMPETENCIES

• Rigorous data-modeling and data-governance discipline.
• Strong analytical and problem-solving skills with attention to data quality and detail.
• Clear communication of data strategy to technical and business stakeholders.
• Outcome orientation — trusted data that measurably enables AI, analytics and personalization.