HYDERABAD · FULLTIME
EY - GDS Consulting - AI And DATA - Databricks Architect - Sr Manager
EYGBS
Hyderabad · onsite · Posted 12d ago
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Undisclosed15–20 yrsfulltimeHyderabad
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Section · 01
About this role
EY-Consulting - Data and Analytics - Databricks Architect - Senior Manager
Job Summary
Responsibilities
Skills And Attributes for Success
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Job Summary
The Senior Delivery Manager Data Architect is a senior client-facing leader accountable for the end-to-end delivery and architectural integrity of complex data, analytics, cloud, and AI transformation programmes. The role combines delivery governance, commercial ownership, stakeholder leadership, and hands-on architecture oversight to translate business priorities into secure, scalable, reliable, and cost-effective data solutions.
The incumbent will act as the single point of accountability for delivery outcomes while defining target-state data architectures, engineering standards, governance controls, and transformation roadmaps. The role requires the ability to move confidently between executive discussions, programme governance, solution design, and technical assurance.
Responsibilities
- Own end-to-end delivery of large, multi-workstream data and analytics programmes from discovery and mobilisation through implementation, transition, and benefits realisation.
- Establish integrated plans, governance forums, delivery cadence, quality gates, dependency management, and executive reporting.
- Manage scope, schedule, budget, capacity, quality, risks, issues, assumptions, and change control; intervene early when delivery deviates from commitments.
- Drive Agile, Scrum, scaled Agile, or hybrid delivery practices appropriate to the client and programme context.
- Lead platform migrations, modernisation initiatives, releases, cutovers, hypercare, and transition to operations with clear readiness and acceptance criteria.
- Maintain delivery transparency using measurable outcomes, milestone health, financial performance, engineering metrics, and value-realisation indicators.
- Define enterprise data strategy, target-state architecture, reference architectures, transition states, and prioritised transformation roadmaps aligned to business and AI objectives.
- Architect modern cloud-native data platforms, including data lakes, lakehouses, warehouses, streaming solutions, data products, semantic layers, APIs, and analytical consumption patterns.
- Lead conceptual, logical, and physical data modelling using dimensional, relational, Data Vault, graph, ontology, and domain-oriented approaches as appropriate.
- Define integration and ingestion patterns for batch, near-real-time, event-driven, CDC, API, and file-based workloads.
- Evaluate platforms, products, and design alternatives; produce architecture decisions, solution blueprints, non-functional requirements, and implementation guardrails.
- Provide architecture assurance across the delivery lifecycle through design reviews, proofs of concept, engineering standards, performance reviews, and technical risk management.
- Ensure solutions meet requirements for scalability, resilience, availability, observability, interoperability, security, privacy, maintainability, and cost optimisation.
- Establish governance principles covering data ownership, stewardship, classification, lineage, metadata, master and reference data, retention, and policy enforcement.
- Embed data quality controls, reconciliation, auditability, privacy-by-design, role-based access, encryption, and regulatory compliance into solution architecture and delivery.
- Partner with cyber security, risk, legal, compliance, and operations teams to ensure controls are demonstrable and audit-ready.
- Build trusted relationships with C-suite sponsors, business leaders, product owners, technology executives, and delivery partners.
- Translate complex business needs into clear solution options, investment cases, roadmaps, and outcome-based delivery plans.
- Facilitate executive workshops, architecture forums, steering committees, and difficult decision-making conversations.
- Own or support proposals, solution shaping, estimates, statements of work, delivery models, contract assumptions, and commercial negotiations.
- Manage programme financials, forecasting, burn, margin, resourcing, vendors, and third-party commitments.
- Identify opportunities for account growth, reusable assets, accelerators, and follow-on transformation initiatives.
- Lead multidisciplinary teams of architects, data engineers, platform engineers, analysts, data scientists, DevOps specialists, quality engineers, and project managers.
- Set clear accountabilities, create a high-performance culture, mentor senior practitioners, and develop succession and capability plans.
- Promote engineering excellence, knowledge sharing, reusable patterns, continuous improvement, and responsible use of data and AI.
- Contribute to hiring, workforce planning, communities of practice, thought leadership, and organisational capability development.
Skills And Attributes for Success
- Bachelor's or master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
- Typically 15+ years of technology experience, including substantial experience delivering enterprise data programmes and operating in a lead data or solution architecture capacity.
- Demonstrable ownership of large, complex, multi-team programmes with responsibility for delivery governance, senior stakeholders, budgets, quality, and commercial outcomes.
- Strong experience designing and delivering cloud data platforms on Microsoft Azure, AWS, or Google Cloud; deep expertise in at least one ecosystem is essential.
- Proven experience with modern data platforms and technologies such as Microsoft Fabric, Azure Data Factory, Azure Databricks, Synapse Analytics, Snowflake, Databricks, Spark, Kafka, cloud object storage, and modern BI tools.
- Advanced knowledge of SQL and strong working understanding of Python or PySpark, data integration, distributed processing, DevOps, CI/CD, infrastructure automation.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
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Section · 02
Skills
CdcAutomationAgileCadenceapisAsset Managementbi toolsamazon web servicesclassificationChange ControlAgile DeliveryAnalyticsCapital MarketscloudArchitectureAzure Data FactoryAzure DatabricksClient SatisfactionMicrosoft AzureArtificial Intelligence
Section · Company
About EY Global Delivery Services ( EY GDS)
EYGBS
Accounting & Auditing
40.0k+
employees
2002
24 years old
Bangalore/Bengaluru, Karnataka
India
₹15.5L PA avg
Avg at EY Global Delivery Services ( EY GDS)
About
EY Global Delivery Services (GDS) is a truly global delivery network of over 74,000 people working across the border to provide innovative and strategic business solutions to EY member firms.
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