Senior Data Architect – North America

Lateral Group

. Assess and shape the Snowflake data platform architecture .

Posted 11/6/2026full-timeRemote • Florida • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Snowflake data platform architecture, including data modeling, ETL/ELT pipeline design, and performance tuning. Proficient in establishing data governance and quality standards while collaborating with cross-functional teams to meet business needs.

Highest-signal resume keywords

Snowflake Data Platform ArchitectureData Modeling SkillsETL/ELT Pipeline DesignAdvanced SQLData Quality and Lineage

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ArchitecturePerformance TuningSchema DesignDimensional ModelingData IngestionData TransformationData GovernanceData CatalogingAI-Enabled Use Cases

Soft Skills

Strong English Communication SkillsSelf-ManagementAbility to Work with Ambiguity

Tools & Technologies

SnowflakeDatabricksDbtAirflowDagster

Industry Keywords

Financial ReportingManagement ReportingData Quality StandardsData LineageDesign Documentation

Tech Stack

Tools & technologies

AirflowCloudETLSnowflakeSQL

About the role

Key responsibilities & impact

Assess and shape the Snowflake data platform architecture
Define target architecture across raw, staging, and mart layers
Establish naming and data-grain standards
Design approaches for corrections and late-arriving data
Model general ledger activity, charts of accounts, and account hierarchies for financial statements and management reporting
Work with finance, investment, and operations stakeholders to translate business needs into scalable data designs
Define ingestion, transformation, and orchestration patterns across 40+ sources
Address data lineage, data quality, and testing
Guide Snowflake warehouse sizing, query performance, and cost management
Run design reviews and produce design documentation, diagrams, decisions, and trade-offs
Mentor data engineers and set technical standards
Shape data governance, data cataloging, and AI-enabled use cases
Participate in interviews and a take-home work trial as part of the hiring process

Requirements

What you’ll need

7+ years in data engineering, data architecture, or database engineering, with ownership of production data platforms
Deep hands-on experience with a cloud data warehouse; Snowflake preferred, Databricks or similar considered
Experience with performance tuning and cost management
Strong data modeling skills, including grain definition, dimensional modeling, layered architectures, corrections, and late-arriving data
Advanced SQL and efficient schema design for high-volume environments
Experience designing ETL/ELT pipelines and integrations across many sources
Experience with dbt or similar transformation frameworks
Experience with Airflow, Dagster, or similar orchestration tools
Experience modeling general ledger data, charts of accounts, and account hierarchies for financial or management reporting
Ability to diagnose and improve platforms not originally built by the candidate
Experience with testing, data quality, lineage, and clear design documentation
Strong English communication skills
Comfort with remote, asynchronous work across time zones
Practical working relationship with AI tools for designing, building, and documenting
Ability to work with ambiguity, shifting priorities, self-management, and continuous feedback

Benefits

Comp & perks

Meaningful products with measurable impact
Support for professional growth, exploring new paths, and greater responsibility
Self-managed, distributed work environment
Flexible asynchronous work across time zones
No burnout or crunch; sustainable high-quality work
Profitable, independent company with over two decades of stability
Variety of projects and fresh challenges
Talented, kind, collaborative team culture
Remote work arrangement