Snowflake Solutions Architect

Codeforce 360; Hyderabad, Bengaluru; On-site; INR 1,400,000 - 2,000,000; Full time

Job summary

Codeforce 360 is seeking a client-facing Snowflake Solutions Architect to lead end-to-end technical solutioning and delivery oversight for Snowflake-based data platform engagements. You will engage with clients, translate requirements into practical designs, and guide teams through ingestion, modeling, governance, and downstream consumption use cases.

The role emphasizes strong design judgment, client communication, and ownership of technical outcomes across the full lifecycle of Snowflake

Qualifications

• 6-9 years of experience in data engineering, data architecture, analytics engineering, or cloud data platform delivery.
• Strong hands-on and architectural experience delivering Snowflake-based solutions in client-facing project or consulting environments.
• Strong command of SQL, data warehousing, dimensional modeling, transformation design, and modern cloud data architecture principles.
• Experience with ETL/ELT and orchestration tools such as dbt, Airflow, Matillion, Informatica, Fivetran, ADF, Glue or similar.
• Strong Python skills for data ingestion, scripting, API integration, automation, utilities, or framework support.
• Experience architecting solutions across APIs, databases, cloud storage, and semi-structured formats.

Responsibilities

• Lead client-facing discovery discussions to understand business goals, data sources, constraints, and governance needs.
• Translate requirements into Snowflake-based solution architectures, approaches, and phased delivery plans.
• Define end-to-end technical approach across ingestion, transformation, modeling, security, and observability.
• Recommend delivery patterns (ETL, ELT, API-based, file-based) suited to client constraints.
• Architect Snowflake solutions across RAW/STAGING/CURATED or Bronze/Silver/Gold with clear ownership and controls.
• Evaluate tools and services across the delivery stack, including orchestration, ingestion, transformation, BI, and AI/ML enablement.
• Define dataflow, transformation boundaries, security controls, and environment strategy across dev/test/prod.
• Estimate technical effort, dependencies, milestones, and realistic timelines.

Skills

Snowflake experience

SQL

Python

Client-facing

Solution architecture

Project estimation

Tools

dbt

Airflow

Matillion

Informatica

Fivetran

ADF

Glue

Job description

We are looking for a client-facing Snowflake Solutions Architect to lead end-to-end technical solutioning and delivery oversight for Snowflake-based data platform engagements. This role is intended for a highly capable architect who can join client discussions, understand business and technical requirements, define practical solution approaches, select appropriate tools and patterns, estimate implementation effort, establish milestones, and remain accountable for the technical success of the engagement from discovery through delivery.

The ideal candidate will have strong hands-on and architectural experience with Snowflake, SQL, Python, ETL/ELT and orchestration tools, cloud and hybrid data integration patterns, and modern analytics ecosystems. This person should be comfortable working directly with client stakeholders, translating ambiguous requirements into clear technical designs and phased delivery plans, and guiding Leads and Developers toward reliable execution across ingestion, transformation, modeling, governance, and downstream consumption use cases.

This role requires strong delivery judgment, strong client communication, strong architecture depth, and the ability to own technical outcomes across the full lifecycle of a Snowflake engagement.

Key Responsibilities

• Lead client-facing discovery discussions to understand business goals, source systems, data constraints, reporting needs, governance requirements, and delivery expectations.
• Translate business and technical requirements into clear Snowflake-based solution architectures, implementation approaches, and phased delivery plans.
• Define the end-to-end technical approach across ingestion, transformation,modeling, data quality, security, observability, and downstream consumption layers.
• Recommend and justify the appropriate delivery pattern for each engagement, including ETL, ELT, API-based ingestion, file-based ingestion, CDC, cloud-native, hybrid, or minimal-ETL approaches as appropriate to client constraints.
• Architect Snowflake solutions across RAW/STAGING/CURATED or Bronze/Silver/Gold patterns with clear separation of responsibilities, environments, and operational controls.
• Evaluate and recommend tools and services across the delivery stack, including orchestration, ingestion, transformation, observability, BI, reverse ETL,and AI/ML-enablement components.
• Define source-to-target architecture, data flow patterns, transformation boundaries, security controls, and environment strategy across development, test, and production.
• Estimate technical effort, identify delivery dependencies, define milestone-based execution plans, and provide realistic timelines aligned to scope and team capacity.
• Break large solution goals into executable workstreams and guide Snowflake Leads and Developers on technical direction, design expectations, and implementation priorities.
• Own end-to-end technical delivery from a solution standpoint, including architectural integrity, scope alignment, delivery readiness, and issue escalation.
• Review solution designs, code patterns, data models, and implementation approaches to ensure they align with the agreed architecture and platform best practices.
• Lead technical decision-making on tradeoffs involving speed, maintainability, scalability, cost, client constraints, source limitations, and operational complexity.
• Provide architectural guidance across structured, semi-structured, API-based,file-based, database, and cloud storage sources.
• Define and govern best practices for Snowflake performance tuning, workload design, security, RBAC, cost management, deployment discipline, and operational reliability.
• Ensure the solution supports downstream BI, analytics, reverse ETL, semantic modeling, AI/ML, and operational use cases as required by the engagement.
• Perform and guide technical R&D on unfamiliar tools, source systems,connectors, architecture patterns, and platform capabilities required to shape or de-risk delivery.
• Use modern AI-assisted engineering and solutioning tools such as ChatGPT,Claude, GitHub Copilot, or similar platforms productively and responsibly for research, prototyping, technical drafting, option analysis,troubleshooting, and acceleration of delivery design.
• Critically validate AI-assisted outputs and ensure all recommended solutions are technically sound, secure, maintainable, and suitable for production delivery.
• Identify technical risks, assumptions, dependencies, data gaps, and operational considerations early and communicate them clearly to internal teams and client stakeholders.
• Contribute to proposal support, pre-sales technical discussions, solution writeups,and delivery planning where needed.
• Provide clear technical status, milestone updates, risks, and recommendations to internal leadership, project stakeholders, and client teams throughout the engagement.

Required Skills & Qualifications

• 6-9 years of experience in data engineering, data architecture, analytics engineering, or cloud data platform delivery.
• Strong hands-on and architectural experience delivering Snowflake-based solutions in client-facing project or consulting environments.
• Strong command of SQL, data warehousing, dimensional modeling, transformation design, and modern cloud data architecture principles.
• Strong experience with one or more ETL/ELT and orchestration tools such as dbt,Airflow, Matillion, Informatica, Fivetran, ADF, Glue, or similar platforms.
• Strong working knowledge of Python for data ingestion, scripting, API integration, automation, utilities, or framework support.
• Experience architecting solutions across APIs, databases, cloud storage, flat files,and semi-structured formats such as JSON, CSV, XML, or similar.
• Familiarity with at least one major cloud platform such as AWS, Azure, or GCP, along with the associated integration and security considerations.
• Strong understanding of Snowflake architecture, workload patterns, performance tuning, security, RBAC, environment design, and cost optimization.