Data Architect - Cloud Data Platform

Job Description :

Key Responsibilities :

Architecture & Technical Leadership :

- Own the overall solution architecture across Data Engineering, Data Platform, and AI/ML workstreams.

- Define and govern reference architectures, design patterns, and technology standards for the engagement.

- Lead technical design reviews, architecture decision records (ADRs), and solution assessments.

- Ensure architectural integrity, scalability, and security compliance across all deliverables.

Client Relationship & Stakeholder Management :

- Act as the primary technical liaison for client's leadership, and business stakeholders.

- Build and sustain trusted advisor relationships through proactive communication and executive-level presentations.

- Translate complex technical concepts into clear business value narratives for C-suite audiences.

- Manage stakeholder expectations, surface risks early, and negotiate scope adjustments collaboratively.

Sprint Governance & Delivery Oversight :

- Lead sprint planning, backlog grooming, and velocity reviews across both the Data and AI tracks.

- Define sprint acceptance criteria and ensure technical quality gates are enforced at each milestone.

- Track delivery against contractual commitments, flagging schedule or quality risks proactively.

- Drive cross-track dependency resolution and coordinate resource allocation with Infogain delivery managers.

Escalation Management :

- Serve as the single escalation point for all client-facing technical and delivery issues.

- Own incident resolution workflows, root-cause analyses, and corrective action plans.

- Facilitate structured escalation paths between Client's stakeholders and Infogain's leadership.

- Mediate technical disagreements within the POD and resolve blockers that impede sprint progress.

Required Skills & Qualifications :

Core Technical Expertise :

- Proven track record designing large-scale cloud data platforms on Azure (Synapse, ADLS Gen2, ADF, Databricks).

- Deep expertise in data warehousing, Lakehouse architectures, and medallion/Lambda/Kappa patterns.

- Hands-on proficiency with PySpark, SQL/T-SQL, dbt, and CI/CD tooling (Azure DevOps / GitHub Actions).

- Solid grounding in AI/ML platform design - MLflow, Azure ML, SageMaker, or equivalent - and integration with enterprise data products.

- Experience with semantic layers, Power BI / Tableau enterprise deployments, and BI governance frameworks.

Architecture & Governance :

- Demonstrated ability to produce and defend ADRs, reference architectures, and data governance frameworks.

- Familiarity with data mesh, data product thinking, and enterprise metadata management (Purview, Alation, or equivalent).

- Knowledge of RBAC, data security, SOX/GDPR compliance patterns in cloud data environments.

Leadership & Communication :

- 15+ years of experience in data engineering, with at least 3 years in client-facing architecture or technical lead capacity.

- Prior experience leading multi-track delivery PODs of 8-15+ engineers and analysts.

- Exceptional stakeholder communication skills - able to engage equally effectively with engineers and C-suite executives.

- Experience operating in consulting or professional services environments is strongly preferred.

Preferred Qualifications :

- Microsoft Certified : Azure Solutions Architect Expert or equivalent cloud certification.

- Exposure to telecom, financial services, or large enterprise data ecosystems.

- Experience with GenAI / LLM integration patterns for enterprise data products.

- Prior onshore POD lead or engagement director experience with North American enterprise clients.