Description

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 GCP 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.

Required Qualifications

• 7+ years of progressive experience in data engineering and solution architecture on enterprise data platforms.
• Strong, hands on experience with GCP data services: BigQuery, Dataflow, Cloud Composer, Dataform, Cloud Storage.
• Expertise across the full data lifecycle: modeling, mapping, transformation design, and data product architecture.
• Strong foundation in dimensional modeling, star schemas, and analytics ready structures.
• Advanced SQL skills for designing and reasoning about complex transformations on large datasets.
• Working knowledge of GCP security and access design (IAM, least privilege, dataset/domain level access).
• Demonstrated ability to operate across architecture and implementation — defining designs, guiding engineers, and reviewing builds.
• Strong communication skills with the ability to explain design decisions to technical and non technical stakeholders.
• Bachelor’s degree in a related field or equivalent experience.

Preferred Qualifications

• Experience with platform modernization or EDW to GCP migration programs.
• Experience in retail, consumer, or omni-channel data domains (customer, product, inventory, orders, pricing, loyalty).
• Familiarity with semantic layer concepts, data catalog/metadata platforms, and governance workflows.
• Exposure to LLM enabled or agentic patterns for AI ready data products.
• Working proficiency in Python for prototyping or pipeline support.
• GCP certifications (Professional Data Engineer or Professional Cloud Architect)

Key Skills

Education

Any Gradute