TELECOMMUTE Enterprise Data Platform Solutions Architect
Role details
Job location
Tech stack
Job description
Strong, hands on Google Cloud Platform experience is essential - including BigQuery, Dataflow, Cloud Composer, Dataform, and Cloud Storage - along with deep expertise in data modeling, mapping, and solution design. Key Responsibilities
- Design end-to-end data solutions for migration waves and net new use cases, covering ingestion, transformation, and consumption layers.
- Develop conceptual, logical, and physical data models aligned to business and analytical needs.
- Define source to target mappings and transformation logic, including handling of data types, nulls, defaults, SCDs, and business rules.
- Make hands on Google Cloud Platform service design decisions across BigQuery, Dataflow, Cloud Composer, Dataform, and Cloud Storage, balancing performance, cost, and security.
- Design dimensional and analytics ready data models (star schemas, fact/dimension structures).
- Apply security and least privilege access principles at the dataset and domain level.
- Partner with Tech Leads and Data Engineers to guide implementation and review builds against design intent.
- Work with Product Managers, Business Analysts, and SMEs to translate requirements into executable solution designs and data product definitions.
- Collaborate with QA/QE teams to ensure quality is designed in - including validation hooks, reconciliation strategy, and data quality expectations.
- Align with platform architecture teams to adopt standards, surface gaps, and contribute reusable patterns.
- Lead solution design reviews and document key decisions, tradeoffs, and rationale.
- Contribute to AI/GenAI enablement where it strengthens solution outcomes (metadata driven workflows, AI ready data products, agentic patterns).
- Operate within Agile delivery models (Scrum/Kanban) using tools such as Jira and Confluence.
Requirements
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7+ years of progressive experience in data engineering and solution architecture on enterprise data platforms.
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Strong, hands on experience with Google Cloud Platform data services: BigQuery, Dataflow, Cloud Composer, Dataform, Cloud Storage.
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Expertise across the full data lifecycle: modeling, mapping, transformation design, and data product architecture.
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Strong foundation in dimensional modeling, star schemas, and analytics ready structures.
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Advanced SQL skills for designing and reasoning about complex transformations on large datasets.
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Working knowledge of Google Cloud Platform security and access design (IAM, least privilege, dataset/domain level access).
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Demonstrated ability to operate across architecture and implementation - defining designs, guiding engineers, and reviewing builds.
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Strong communication skills with the ability to explain design decisions to technical and non technical stakeholders.
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Bachelor's degree in a related field or equivalent experience. Preferred Qualifications
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Experience with platform modernization or EDW to Google Cloud Platform migration programs.
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Experience in retail, consumer, or omni-channel data domains (customer, product, inventory, orders, pricing, loyalty).
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Familiarity with semantic layer concepts, data catalog/metadata platforms, and governance workflows.
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Exposure to LLM enabled or agentic patterns for AI ready data products.
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Working proficiency in Python for prototyping or pipeline support.
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Google Cloud Platform certifications (Professional Data Engineer or Professional Cloud Architect). Team & Culture Fit
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Pragmatic problem solver who balances speed vs. durability and innovation vs. standardization.
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Collaborative and outcome driven - works closely with engineering, product, BA, and quality teams.
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Strong ownership mindset - identifies gaps, proposes solutions, and drives alignment.
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Comfortable with ambiguity and multi wave delivery across multiple pipelines.
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Clear, concise communicator who can tailor messaging to engineers and executives.