Key Responsibilities

Client Engagement &

- Solution Shaping

- Engage directly with client stakeholders

Engage directly with client business and technology stakeholders to understand their domain, operating model, pain points, and strategic goals.

- Translate ambiguous business problems

Translate ambiguous business problems into clear architecture requirements, success metrics, and phased delivery plans.

- Run discovery workshops

Run discovery workshops, present architecture proposals, and defend design choices in front of both technical and non-technical audiences.

- Act as the trusted data advisor

Act as the trusted data advisor across the engagement lifecycle — pre-sales, solutioning, delivery oversight, and post-go-live optimisation.

Architecture &

- Data Modelling

- Own the target-state architecture

Own the target-state architecture: conceptual, logical, and physical designs for data platforms, including integration patterns and consumption layers.

- Design data models

Design data models appropriate to the problem — dimensional (Kimball), Data Vault, or domain-driven — and justify the choice.

- Define reference architectures

Define reference architectures and architecture decision records (ADRs); establish patterns that multiple delivery teams can reuse.

- Evaluate tooling and platform trade-offs

Evaluate tooling and platform trade-offs; recommend the right fit for the client's maturity, scale, and budget rather than defaulting to a single stack.

Delivery on Microsoft Fabric

- Shape solutions on Microsoft Fabric

Shape solutions on Microsoft Fabric — OneLake, Lakehouses, Warehouses, Data Factory, Dataflows Gen2, Spark notebooks, Real-Time Intelligence, and Power BI semantic models — at a design and oversight level.

- Define the medallion architecture

Define the medallion architecture (Bronze / Silver / Gold), data contracts,



and Delta Lake / partitioning strategies for each engagement.

- Guide the delivery team

Guide the delivery team on capacity sizing (F-SKUs), workload isolation, and cost / performance optimisation. You will review and direct, not write every pipeline.

Governance, Security &

- Quality

- Architect secure, governed platforms

Architect secure, governed platforms using Microsoft Purview, workspace roles, row-level and object-level security, sensitivity labels, and lineage.

- Define data quality frameworks

Define data quality frameworks, testing strategies, and observability approaches that scale across domains.

- Ensure compliance

Ensure compliance with relevant standards (GDPR, HIPAA, DPDP, or industry-specific) as part of every design.

Capability Building

- Mentor data engineers, analysts, and junior architects

Mentor data engineers, analysts, and junior architects; raise the design quality of the broader practice.

- Contribute to internal accelerators

Contribute to internal accelerators, reference architectures, and practice-level IP.

- Support pre-sales

Support pre-sales — RFP responses, solution estimates, and PoCs — as part of the Capability function.

Required Qualifications

- Up to 14 years of total experience

Up to 14 years of total experience, with the last several years spent in an architecture or lead-solutioning capacity — not purely in hands-on engineering.

- Track record across more than one platform





Demonstrable track record of designing end-to-end data solutions across more than one platform over your career (for example, combinations of Azure Synapse, Databricks, Snowflake, AWS Redshift, GCP BigQuery, Teradata, or on-prem warehouses).

- Working proficiency in Microsoft Fabric

Working proficiency in Microsoft Fabric at an architecture and design level.

Strong

Azure data stack experience (Synapse, ADF, Databricks, Power BI) with active Fabric adoption is acceptable.

- Strong data modelling credentials

Strong data modelling credentials — able to defend dimensional, Data Vault, and normalised designs and pick the right one for the context.

- Fluent in SQL and comfortable reading PySpark / Python

Fluent in SQL and comfortable reading PySpark / Python; you will review and challenge code, even if you are not the primary author on most engagements.

- Robust grounding in data governance

Strong grounding in data governance, security, lineage, and compliance.

- Excellent client-facing communication

Excellent client-facing communication — able to lead workshops, present to CXOs, and produce crisp architecture documents in English.

- Willingness to work on-site

Willingness to work on-site from our Gurgaon office and travel to client locations as required.

Good to Have

- Microsoft certifications: DP-600, DP-700, or broader architecture certifications (Azure Solutions Architect, TOGAF, DAMA-CDMP).

- Experience with dbt, Delta Lake internals, and open table formats (Iceberg, Hudi).

- Domain depth in one of: healthcare / life sciences, BFSI, retail &
- CPG, or manufacturing.

- Exposure to open-source or community-driven data models and standards relevant to your domain (for example, OMOP or FHIR in healthcare).

- Pre-sales experience — responding to RFPs, building PoCs, and estimating data programmes.

📌 Data Architect (Gurugram)
🏢 Infinit-O
📍 Gurugram