Data Platform Engineer – Operations & AI Modernization

Data Platform Engineer - Operations & AI Modernization

We are looking for a highly motivated and hands-on Data Platform Engineer who is passionate about modern data technologies, automation, and AI and wants to take meaningful ownership of enterprise-scale data platforms.

This role will focus primarily on Snowflake, Talend, data engineering, platform reliability, and modernization of DataOps while also contributing to strategic data and analytics initiatives.

The role is supported by an established global operations team providing 24x5 platform monitoring and routine operational support. The onsite engineer will focus on technical ownership, complex problem solving, platform improvements, automation, new engineering initiatives, and critical U.S. business-hours escalations rather than routine monitoring activities.

You will work closely with experienced Data Engineering leaders and global delivery teams, gaining exposure to enterprise data architecture, business-critical data platforms, client delivery, and emerging AI technologies.

This is an excellent opportunity for an ambitious engineer who wants to grow beyond traditional development or production support into platform ownership and technical leadership.

What You’ll Do

• Develop deep technical and functional knowledge of enterprise Snowflake and Talend platforms and progressively become a trusted technical owner for these environments.
• Serve as an onsite technical escalation point for complex or business-critical Snowflake, Talend, data integration, and data platform issues during U.S. business hours.
• Lead technical investigation and root-cause analysis for significant issues involving data availability, data quality, pipeline reliability, integrations, platform performance, and downstream analytics dependencies.
• Identify recurring issues and engineer long-term solutions rather than relying on repeated manual intervention.
• Drive improvements in platform reliability, observability, performance, automation, and operational resilience.
• Contribute hands-on to new Data Engineering and Analytics initiatives involving Snowflake, Talend, data pipelines, integrations, cloud technologies, and enterprise analytics solutions.
• Build a strong understanding of the end-to-end enterprise data ecosystem, including source systems, integrations, data pipelines, Snowflake, downstream analytics platforms, and critical business processes.
• Develop automation and tooling that reduces manual operational effort and improves engineering productivity.
• Explore practical applications of AI and intelligent automation for DataOps, including AI-assisted incident analysis, anomaly detection, root-cause identification, proactive issue detection, operational knowledge management, and intelligent monitoring.
• Evaluate emerging data and AI technologies and identify practical opportunities to improve platform reliability, developer productivity, and operational efficiency.
• Create and continuously improve technical documentation, operational runbooks, architecture knowledge, troubleshooting procedures, and platform knowledge repositories.
• Communicate effectively with technical teams, business users, and client stakeholders regarding significant technical issues, business impact, risks, and resolution plans.
• Take increasing ownership of technical workstreams and projects as platform and business knowledge grows.

What We’re Looking For

We are looking for someone with strong technical fundamentals, but equally important are curiosity, ownership, accountability, and the desire to continuously learn.

Required Qualifications

• 3-5 years of experience in Data Engineering, Data Integration, Data Warehousing, Analytics Engineering, or related areas.
• Strong hands-on SQL skills with the ability to analyze and troubleshoot complex data issues.
• Experience with Snowflake or another modern cloud data platform.
• Experience with Talend or another enterprise ETL/data integration platform.
• Solid understanding of ETL/ELT architecture, data pipelines, integrations, data warehousing, and data quality concepts.
• Experience developing, troubleshooting, or supporting enterprise data solutions.
• Strong analytical and problem-solving skills.
• Demonstrated ability to independently investigate technical problems and drive them toward resolution.
• Strong desire and ability to learn new technologies quickly.
• Good verbal and written communication skills.

Preferred Qualifications

• H…