Data Architect

About the Data Architect Position

At Verndale, we are building a next‑generation Data & Analytics practice designed to help organizations transform their complex data ecosystems into engines of clarity and intelligent action. Our vision is to empower clients to unlock hidden opportunities, optimize operations, and accelerate profitable growth through modern data architectures, trusted data management, advanced analytics, and AI‑driven solutions. As part of a digital experience services firm with a strong heritage in customer experience and marketing technology, our Data & Analytics team extends Verndale’s core capabilities to deliver seamlessly integrated, insight‑driven solutions that fuel personalization, operational excellence, and strategic foresight.

We are pragmatic innovators, grounded in Verndale’s entrepreneurial culture, who design scalable, well‑governed data platforms and embed intelligence into business workflows, enabling clients to thrive in the era of generative AI and beyond.

What You’ll Do

• Architect and design modern cloud‑based data platforms (Snowflake, Databricks, AWS, Azure, GCP) that support enterprise‑scale analytics, AI/ML, and digital experience solutions.

• Define logical and physical data models, dimensional models, data standards, and architecture blueprints to ensure scalability, reliability, and security.

• Lead the design and implementation of data ingestion, integration, and transformation pipelines (ETL/ELT) leveraging tools like dbt, Fivetran, or equivalent.

• Partner with clients to assess current‑state architectures, identify pain points, and design future‑state roadmaps aligned with their business objectives.

• Establish and enforce data governance, metadata management, and data quality frameworks to ensure trusted, well‑documented, and compliant data assets.

• Collaborate with analytics leads, engineers, and client stakeholders to translate complex requirements into actionable, sustainable solutions.

• Drive innovation in data & AI strategy: assess emerging technologies (e.g. GenAI, RAG, MLOps) and help incorporate them into client or internal roadmaps.

• Support proof‑of‑concept initiatives, platform evaluations, and migration strategies (e.g., legacy data warehouse to cloud) with a focus on speed‑to‑value.

• Participate in pre‑sales and client workshops, contributing architecture expertise to solution shaping, scoping, and estimation.

• Mentor engineers and analysts, providing architectural oversight to ensure delivery excellence.

What We’re Looking For

• 7 years of experience in data architecture, engineering, or solution design, with demonstrated success delivering modern data platforms at scale.

• Strong expertise in cloud data platforms (Snowflake, Redshift, Big Query, Databricks, Synapse) and modern data ecosystem components (streaming, orchestration, MDM, cataloging).

• Proficiency in designing end‑to‑end architectures, including ingestion, storage, processing, semantic layers, and analytics enablement.

• Hands‑on skills in SQL, Python, or Java; experience with distributed processing frameworks (e.g., Apache Spark, Presto, EMR).

• Design and implement scalable data architecture using Medallion Architecture (Bronze, Silver, Gold layers) to transform raw data into curated, business‑ready datasets.

• Familiarity with containerization and orchestration (Kubernetes, Docker, ECS) and modern workflow tools (Airflow, dbt, Dagster).

• Experience implementing data security, compliance, and governance standards (RBAC, data privacy regulations, lineage, observability).

• Exposure to big data frameworks like Spark (PySpark), Hadoop ecosystem, Flink, or similar.

• Proven ability to lead client‑facing workshops, communicate tradeoffs, and gain alignment on solution design.

• Leverage generative AI tools (e.g., ChatGPT, Gemini, Claude) to accelerate solution design, documentation, and architecture decision‑making.

• Experience working in consulting or digital services environments, balancing technical rigor with pragmatic delivery.

Nice‑to‑Have Skills

• Exposure to DXP ecosystems (Sitecore, Optimizely, Salesforce Marketing Cloud) and integrating marketing/customer data platforms.

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