Solutions Architect - Data Engineering

New

Remote-first opportunity for candidates based in India., Collaborate effectively with distributed colleagues and client teams across multiple time zones.Full-TimeSenior

Salary not disclosed

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Job Details

Experience: 8+ years of experience
Required Skills: AWSPythonSQLMicrosoft AzureSnowflakeData engineeringDatabricksLangChain

Requirements

8+ years of experience in Solutions Architecture, Data Engineering, software engineering, or related technical consulting roles.
Proven experience designing and delivering enterprise Data & AI solutions into production within cloud environments.
Strong consulting background, including experience leading technical discovery, solution architecture, stakeholder discussions, and client-facing engagements.
Demonstrated experience using modern AI technologies throughout the software delivery lifecycle to improve architecture, engineering productivity, code quality, testing, documentation, troubleshooting, and business outcomes.
Hands-on experience with several modern cloud and data platforms, such as Snowflake, Databricks, Google BigQuery, AWS, Microsoft Azure, and Google Cloud Platform.
Strong data engineering experience with technologies such as Python, SQL, Java and/or Scala, Spark, Kafka, Airflow, dbt, Fivetran, Matillion.
Experience with modern engineering practices including CI/CD, Infrastructure as Code, observability, monitoring, and automated delivery.
Practical experience incorporating AI into engineering and solution delivery using technologies such as Anthropic Claude, OpenAI, GitHub Copilot, Microsoft Copilot, Google Gemini, Snowflake Cortex AI, AWS Bedrock, LangChain, LangGraph.
Strong understanding of cloud architecture, data platforms, distributed systems, data pipelines, and production engineering practices.
Excellent problem-solving and analytical skills, with the ability to navigate ambiguity and make sound architectural trade-offs.
Strong communication and presentation skills, with the ability to influence technical leaders, executives, engineers, and other stakeholders.
Demonstrated technical leadership, mentoring, and team collaboration skills.

Responsibilities

Lead client discovery sessions to understand business objectives, technical requirements, constraints, and opportunities, translating complex challenges into scalable Data & AI architectures.
Act as a trusted technical advisor throughout client engagements, helping stakeholders make informed architectural and technology decisions.
Design enterprise-grade Data & AI solutions and provide recommendations on architecture, tooling, implementation approaches, and technical trade-offs.
Create architecture diagrams, technical design documentation, implementation plans, standards, and other materials required to guide successful delivery.
Own solution delivery from architecture and design through production deployment, working closely with engineering teams to maintain quality, scalability, and reliability.
Identify technical risks, dependencies, and delivery blockers early and drive practical solutions to keep projects moving.
Apply AI throughout the software development lifecycle to improve solution design, engineering productivity, documentation, testing, code quality, troubleshooting, and client outcomes.
Advise clients on practical and responsible adoption of AI technologies within their data and engineering environments.
Provide architectural guidance, technical coaching, design reviews, and mentorship to engineers throughout project delivery.

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