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Job Description & How to Apply Below
At Shyft Labs, we live and breathe data. Since 2020, we’ve been helping Fortune 500 companies unlock growth with cutting‑edge digital solutions that transform industries and create measurable business impact. We’re growing fast and we’re looking for passionate problem‑solvers who are ready to turn big ideas into real outcomes.
The Opportunity
We’re looking for a Data Architect to lead the design and evolution of a Customer Data Mart that powers CDP, analytics, marketing activation, and reporting use cases. This role is for a senior technical leader who brings architectural clarity to complex customer data ecosystems, owns execution end‑to‑end, and sets the technical direction for scalable, secure, and resilient data platforms.
As a Data Architect, you will partner closely with client stakeholders, marketing teams, product leaders, and engineering teams to design and implement modern, cloud‑native data architectures. You will operate as both a hands‑on architect and a strategic advisor, shaping long‑term data strategy while remaining deeply involved in technical implementation.
This role is best suited for a candidate possessing a robust foundation in data engineering and architecture, extensive experience with enterprise‑scale data systems, and a proven capability to manage ambiguity while implementing structured, long‑term solutions.
What You’ll Be Doing
Own the technical vision and architecture for the Unified Customer Data Mart, ensuring solutions are scalable, secure, compliant, and aligned with enterprise standards.
Design and implement end‑to‑end data architectures of data pipelines, including raw data ingestion (Bronze), data cleaning and standardization (Silver), and curated data marts (Gold) that serve CDP, reporting, and activation use cases.
Define and evolve data modeling standards for customer data, including customer dimensions, transaction facts, engagement events, web behavior, support interactions, and loyalty activity. Establish naming conventions, schema patterns, and architectural best practices across the customer data domain.
Decomposing complex business requirements into structured technical solutions and driving alignment with client stakeholders.
Formulate, compare, and present multiple architectural approaches for data ingestion, transformation, identity resolution, and consumption patterns, guiding clients and internal teams toward optimal long‑term solutions that balance speed, maintainability, and scalability.
Architect and build production‑grade data pipelines using DBT and Airflow that support customer analytics, segmentation and reporting at scale.
Partner directly with client stakeholders to understand business objectives, translate customer journey requirements into robust technical designs, and act as a trusted technical advisor on data architecture decisions.
Lead and mentor cross‑functional teams , including Analytics Engineers, Data Engineers, and BI developers, setting a high bar for technical quality, code review standards, and documentation practices.
Influence and contribute to data governance initiatives , including PII handling, data quality frameworks, identity resolution strategies, and platform reliability. Define RLS policies, data retention rules, and compliance patterns.
Drive the development of reusable frameworks and accelerators for customer data pipelines, including DBT macros, Airflow DAG patterns, and data quality tests that can be applied across multiple sources and brands.
Contribute to technical strategy and roadmap planning for the building data mart, including source prioritization, and integration with downstream systems (CDP, ESP, reporting tools).
What You Bring
Deep expertise in SQL and Python , with demonstrated ability to design, optimize, and troubleshoot complex distributed data systems.
5+ years of experience in data engineering and/or data architecture, with a proven track record of building and scaling enterprise‑level data platforms.
Extensive experience designing and implementing data lakes, cloud data warehouses, and modern analytics architectures in production environments.
Hands on experience with DBT for…
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