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phData

Managed data engineering and ML solutions

Principal Solutions Architect - Data Engineering

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • At least 10 years of experience in Solutions Architecture, Data Engineering, or related consulting roles, including experience as a senior technical leader across complex enterprise client accounts.
  • Proven experience designing and delivering enterprise Data and AI solutions into production within cloud environments, while owning technical strategy and outcomes across multiple projects, workstreams, or client initiatives.
  • Demonstrated experience delivering with AI and using modern AI technologies throughout the software delivery lifecycle to improve solution design, engineering productivity, code quality, testing, documentation, troubleshooting, and client outcomes.
  • Strong consulting experience leading technical discovery, solution architecture, executive client engagements, and account growth, including identifying opportunities, shaping solutions, contributing to proposals and statements of work, and helping generate revenue within existing or new client relationships.
  • Hands-on experience with many of the following cloud and data platforms: Snowflake, Databricks, Google BigQuery, Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
  • Hands-on experience with data engineering technologies such as Python, SQL, Java and/or Scala, Spark, Kafka, Airflow, dbt, Fivetran, and Matillion, or similar technologies.
  • Experience with modern engineering practices including continuous integration and continuous delivery, Infrastructure as Code, observability, and monitoring.
  • Experience incorporating AI into day-to-day engineering and solution delivery using technologies such as Anthropic Claude, OpenAI, GitHub Copilot, Microsoft Copilot, Google Gemini, Snowflake Cortex AI, AWS Bedrock, LangChain, LangGraph, or similar enterprise AI development platforms and frameworks.

Responsibilities

  • Lead strategic discovery across client accounts to uncover business priorities, technical challenges, and emerging opportunities, translating them into scalable Data and AI architectures, roadmaps, and opportunities for expanded client engagement.
  • Serve as a senior technical advisor and trusted partner to client executives and technical leaders, helping shape account strategy, strengthen relationships, and identify opportunities where the company can deliver additional value.
  • Provide recommendations on architecture, tooling, implementation approaches, and technical trade-offs; shape solution strategy; scope new opportunities; contribute to proposals and statements of work; and partner with account and sales leaders to convert client needs into revenue-generating engagements.
  • Lead and oversee delivery of enterprise Data and AI solutions across strategic accounts, ensuring architectural quality and client outcomes while guiding engineering teams, identifying technical and account risks, and connecting successful delivery to continued account growth.
  • Use AI throughout the software delivery lifecycle to improve solution design, engineering productivity, documentation, testing, troubleshooting, and client outcomes, and help clients identify and prioritize practical AI opportunities for broader transformation initiatives.
  • Mentor architects and engineers through architectural guidance, technical coaching, and design reviews; contribute to hiring, onboarding, and technical enablement; and raise the technical and consulting capabilities of the broader organization.

Desired Qualifications

  • Industry certifications across Snowflake, AWS, Azure, Google Cloud Platform, Anthropic, and/or Databricks.
  • Contributions to technical communities through speaking, writing, open source, or internal enablement.

About the Company

phData

Managed data engineering and ML solutions

phData provides data engineering, data strategy, and machine learning solutions through end-to-end managed services and consulting for enterprises. It delivers cloud data engineering, data migrations, business intelligence, and ML applications by combining data infrastructure automation with analytics and AI strategy in project-based engagements and ongoing support. It differentiates itself by offering full, service-led delivery focused on sustainable data engineering practices and strong customer success, plus its status as an AWS consulting partner with specialized cloud analytics and ML expertise on AWS. Its goal is to help clients turn data into actionable insights and sustainable growth by building scalable data platforms and AI systems guided by clear roadmaps.

Company size
501-1,000
Company stage
Seed
Total funding
$2.5M
Headquarters
Minneapolis, MN
Founded
2014

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