Senior Data Architect, Blend

Salary not provided

USD 85 - USD 95 - hourly

AWS

Python

Athena

Expert level

Remote from US

Business performance data & analytics

Be an early applicant

Business performance data & analytics

501-1000 employees

B2BArtificial IntelligenceAnalyticsSaaSData Analysis

Be an early applicant

Salary not provided

USD 85 - USD 95 - hourly

AWS

Python

Athena

Expert level

Remote from US

501-1000 employees

B2BArtificial IntelligenceAnalyticsSaaSData Analysis

Company mission

To help advance our understanding of our customers and business performance.

Job

Company

Role

Who you are

Strong experience with AWS data services including:
AWS Glue
Amazon S3
AWS Lake Formation
Amazon Athena
Deep expertise in modern data lake architecture and large-scale data ingestion frameworks
Experience designing CDC and streaming-based ingestion patterns
Strong understanding of data contracts, schema management, and data governance principles
Advanced experience with Python and PySpark
Strong knowledge of distributed data processing and cloud-native architecture patterns
Ability to create clear architectural documentation and implementation specifications for engineering teams
10+ years of experience in data engineering, data platform architecture, or related disciplines
3+ years serving in a Data Architect or Solution Architect capacity
Experience working in large enterprise environments with complex, multi-source data ecosystems
Experience supporting marketing, customer, or analytics-focused data platforms preferred
Telecommunications industry experience is a plus

What the job involves

We are looking for a highly skilled Data Architect to lead architecture design for a large-scale Marketing Data Layer initiative supporting a major telecommunications provider
This role will be responsible for defining scalable ingestion frameworks, modern data lake architecture, and data integration standards that enable reliable, near-real-time marketing data access across the enterprise
This is an opportunity to shape a high-impact AWS-based data ecosystem while partnering closely with client stakeholders, data engineering teams, and cross-functional business leaders
Design and own the ingestion architecture that moves data from 20+ enterprise source systems into the AWS Marketing Data Layer
Define scalable ingestion patterns for both legacy and direct source integrations across 18 business and data domains
Architect and document data contracts between source systems and the data layer, including:
Schema standards and versioning
SLAs and freshness expectations
Data quality and governance requirements
Design and optimize AWS S3 data lake structures, including:
Raw, staged, and curated zones
Partitioning and storage strategies
Lake Formation access controls and governance policies
Define Change Data Capture (CDC) and streaming ingestion patterns to support near-real-time data freshness requirements
Translate conceptual and logical architecture into detailed, implementable technical specifications for distributed and nearshore Data Engineering teams
Partner with engineering leadership and client stakeholders to ensure scalability, performance, maintainability, and operational excellence across the platform
Provide technical leadership and architectural guidance throughout the delivery lifecycle
What Makes You Successful
You are systems-oriented and think strategically about scalability, reliability, and long-term maintainability
You can balance architecture vision with hands-on technical depth
You communicate complex technical concepts clearly to both engineering and business stakeholders
You thrive in collaborative, fast-moving consulting environments
You bring a product mindset to enterprise data platforms and care deeply about operational excellence

Our take

As large enterprises race to digitize everything from supply chains to customer service, they're drowning in data, but not always insights. So, that's where Blend comes it, helping businesses turn messy, underused data into something genuinely useful, applying advanced analytics and AI to drive smarter decisions rather than just prettier dashboards.

Made up of data scientists and engineers, Blend works behind the scenes to make machine learning actually function in the real world. Fro, from AI integration to data governance and MLOps. Essentially, it helps big companies get more value out of the information they already have, improving efficiency and making data a competitive advantage rather than a compliance headache.

Backed by a 2022 Growth Equity investment, Blend has expanded through smart acquisitions, including FutureproofAI, which broadened its AI capabilities and client reach, and Montevideo Labs, strengthening its footprint in Latin America.