TalentXM is seeking an experienced Manufacturing Data Engineer to support AI-enabled manufacturing engagements for a US-based client. This is a fully remote freelance opportunity, with a preference for candidates based in India.
This role is ideal for a hands-on data engineering professional with strong experience in industrial data pipelines, real-time streaming, smart factory environments, and modern cloud data platforms. The Manufacturing Data Engineer will help translate manufacturing requirements into scalable technical workflows, support AI and automation initiatives, and contribute to reusable assets that improve delivery speed and client outcomes.
The ideal candidate combines strong data engineering capabilities with practical manufacturing domain knowledge, including Industry 4.0, OT/IT integration, MES, ERP, quality, maintenance, production operations, and smart factory concepts.
Key Responsibilities
- Own the core responsibilities of the Manufacturing Data Engineer role across client manufacturing AI engagements.
- Work with cross-functional pods spanning US client-facing leadership, India AI/data engineering, and LATAM manufacturing or vision specialists.
- Translate manufacturing requirements into clear technical, workflow, delivery, or GTM execution plans.
- Partner with stakeholders including plant leaders, CIO/CDO teams, operations leaders, quality teams, maintenance teams, and TalentXM delivery leadership.
- Document decisions, assumptions, workflows, risks, and reusable playbooks in a way that supports asynchronous global collaboration.
- Contribute reusable templates, assets, automations, prompts, architectures, demos, or sales enablement material to TalentXM's internal accelerator library.
- Use measurable success criteria tied to manufacturing outcomes such as OEE, downtime, scrap reduction, quality accuracy, response time, pipeline growth, renewal, or adoption.
- Follow TalentXM's accountability, growth mindset, and flexible work operating model while maintaining high client trust.
Required Skills & Experience
- 8–10 years of relevant experience in data engineering, manufacturing data platforms, industrial IoT, or smart factory technology.
- Hands-on experience with real-time streaming and industrial data protocols, including:
-Kafka or Kinesis
-MQTT
-OPC-UA / OPC
- Strong experience with modern data platforms such as:
-Databricks
-Snowflake
-Azure, AWS, Google Cloud, or equivalent enterprise cloud platforms
- Strong written communication and async documentation
- Ability to work with global fractional pods and outcome-based delivery models
Manufacturing / Domain Knowledge
- Awareness of smart factory, Industry 4.0, OT/IT, MES, ERP, quality, maintenance, and production operations concepts.
- Ability to understand discrete and/or process manufacturing workflows depending on client context.
- Comfortable speaking with both technical teams and business stakeholders.
AI / Automation Expectations
- Operate at the Integrator level for AI readiness.
- Use AI tools responsibly for research, documentation, workflow acceleration, analysis, and delivery quality.
- Understand where AI should automate work, augment experts, or support decision-making without overpromising.
Preferred Tools / Platforms
- Zoho Recruit / Zoho CRM / Zoho Projects for TalentXM operations
- Microsoft Azure, AWS, Google Cloud, Databricks, Snowflake, or equivalent enterprise platforms
- Workato, n8n, Power Automate, MuleSoft, Boomi, APIs, webhooks, and integration workflows where relevant
- GitHub, Jira/Azure DevOps, documentation tools, Loom, Slack/Teams, and collaborative delivery systems
Example Projects
- Manufacturing AI discovery and roadmap for a mid-market manufacturer with prioritized 90-day use cases.
- AI-enabled quality, maintenance, operations, or sales workflow that creates measurable ROI for a client.
- Reusable TalentXM accelerator, template, demo, or playbook that helps the next pod deliver faster.
KPIs / Success Measures
- 90-day role ramp-up with clear contribution to active pipeline, delivery, bench readiness, or productized offerings.
- Quality of documentation, stakeholder confidence, and measurable business outcomes.
- Client satisfaction, internal pod collaboration, and ability to turn work into repeatable TalentXM IP.
Certifications
- Preferred: AWS ML Specialty, Azure AI Engineer, Azure/AWS Solutions Architect, NVIDIA certifications, Databricks, Snowflake, ISA CAP, Workato Automation Pro, or relevant manufacturing vendor certifications.
- Equivalent hands-on project experience may be accepted when supported by strong examples and references.
