Solution Architect-Data

About USEREADY

USEReady helps enterprises apply AI and agentic intelligence to improve decisions, automate operations, and build smarter, more autonomous business systems.

For more than a decade, we have built the foundations that make this possible by modernizing BI environments, migrating legacy platforms, improving data quality, and enabling governed, cloud-first architectures. These foundations now support the next step: AI-driven insights, automated intelligence, and agent-powered decision support that reduce complexity and accelerate outcomes.

We work closely with technology leaders such as AWS, Elementum, Snowflake, Tableau, Databricks, and others to help organizations modernize analytics, strengthen governance, and deploy agentic automation with confidence. We founded in 2011 and Headquartered in New York City with 450+ experts across the United States, Canada, India, and Singapore, we serve industries including financial services, healthcare, manufacturing, government, education, and retail. Our deep expertise, player-coach delivery model, and focus on fast, measurable results make us a trusted partner for building an AI-ready enterprise.

About the Role

We are looking for aSenior Data Platform & Analytics Presales Architect with 12+ years of experience across data engineering, data platforms, analytics, and technical solutioning.

The ideal candidate will own thetechnical solutioning and presales lifecycle for data platform and analytics engagements. This role involves working directly with prospects and business stakeholders, understanding complex data challenges, defining scalable target architectures, developing technical proposals, estimating effort and timelines, and ensuring that solutions proposed during presales are practical, commercially viable, and deliverable.

You will work closely with sales, delivery, architecture, and technology teams to shape compelling solutions across modern data platforms, cloud data engineering, analytics, and BI.

Key Responsibilities

• Leadtechnical discovery sessions with CDOs, data leaders, architects, and engineering teams to understand current-state environments, business challenges, data landscapes, and transformation objectives.

• Translate complex and fragmented environments—includinglegacy data warehouses, reporting systems, undocumented data lineage, and disparate data sources—into scalable and defensible target architectures.

• Own the technical response forRFPs, RFIs, proposals, and solution presentations, including architecture, technical approach, assumptions, risks, effort estimates, timelines, and delivery sequencing.

• Design moderndata platform and analytics architectures covering data ingestion, transformation, storage, data modeling, semantic layers, orchestration, data quality, governance, and consumption.

• Develop solutions usingLakehouse, Data Warehouse, Medallion Architecture, dimensional modeling, and other modern data architecture patterns.

• Lead and supportproofs of concept (PoCs), technical workshops, demonstrations, and solution presentations, focusing on solving complex business and technical challenges.

• Assess and estimatedata migration and modernization initiatives, including on-premises to cloud, SQL Server to Snowflake, legacy warehouse modernization, and migration from legacy BI platforms to modern analytics solutions.

• Develop realistic estimates by consideringdata volumes, complexity, dependencies, lineage gaps, undocumented business logic, integration requirements, and delivery risks.

• Partner with delivery leadership and engineering teams to ensure that proposed solutions aretechnically feasible, appropriately staffed, commercially viable, and aligned with delivery capabilities.

• Collaborate with sales teams to articulate thebusiness value, technical benefits, architecture, implementation approach, and differentiators of proposed solutions.

• Leverage partner technologies and platforms such asSnowflake, Databricks, Tableau, and Power BI where they provide genuine value to the solution.

• Provide technical guidance and mentorship to architects, data engineers, and presales team members.

• Participate in client presentations and confidently communicate technical solutions to bothexecutive stakeholders and hands-on engineering teams.

Required Skills & Experience

• 12+ years of overall experience in data engineering, data platforms, analytics, architecture, or technology consulting.

• At least5+ years of experience in solution architecture, technical presales, consulting, or solutioning.

• Strong hands-on experience in at leasttwo or more of the following:

  • Snowflake

  • Databricks

  • Azure Data Services

  • AWS Data Services

  • dbt

  • Apache Airflow

  • Apache Spark

• Strong understanding ofmodern data architecture and engineering principles, including:

  • Data ingestion and integration

  • ETL/ELT

  • Data warehousing

  • Lakehouse architecture

  • Medallion architecture

  • Dimensional modeling

  • Data orchestration

  • Data quality

  • Data governance

  • Semantic/data consumption layers

• Working knowledge of modernBI and analytics platforms, with strong expertise inTableau or Power BI preferred.

• Proven experience preparingtechnical estimates, effort sizing, project plans, assumptions, and delivery approaches that were subsequently executed by delivery teams.

• Strong understanding ofdata migration and modernization programs, including legacy-to-cloud and legacy BI modernization.

• Excellent analytical and problem-solving skills with the ability to translatebusiness requirements into practical technical solutions.

• Strong client-facing and presentation skills with the ability to communicate effectively withCXO/CDO-level stakeholders as well as technical engineering teams.

• Ability to lead technical discussions, challenge assumptions, manage ambiguity, and influence solution decisions.

• Strong written and verbal communication skills.

Good to Have

• Experience inOil & Gas, Manufacturing, Banking/Financial Services, or other enterprise domains.

• Certifications inSnowflake, Databricks, Microsoft Azure, or AWS.

• Experience working in aconsulting, systems integrator, IT services, or digital transformation organization.

• Experience working with multiple cloud platforms and modern data ecosystem technologies.

• Experience in developingreusable solution accelerators, reference architectures, frameworks, and PoC assets.

• Experience supporting large enterprise transformation and data modernization programs.