Data Platform Engineer – Operations & AI Modernization

Fipsar Inc; Hillsborough Township (NJ); On-site; USD 110,000 - 160,000; Full time

Job summary

Fipsar Inc in the United States is seeking a Data Platform Engineer to own and modernize enterprise data platforms, focusing on Snowflake and Talend, platform reliability, and automation. You will work with global teams to deliver data engineering solutions and AI-enabled DataOps initiatives.

The role involves technical ownership, problem solving, and collaboration across data engineering leaders, with opportunities to grow into leadership positions as you expand expertise in Snowflake, Talend,

Qualifications

• 3-5 years of experience in data engineering, data integration, or data warehousing.
• Strong SQL skills and ability to troubleshoot complex data issues.
• Experience with Snowflake or similar cloud data platform.
• Experience with Talend or other ETL/data integration tools.
• Solid understanding of ETL/ELT, data pipelines, and data quality concepts.

Responsibilities

• Develop deep technical knowledge of enterprise Snowflake and Talend platforms and own these environments.
• Serve as onsite escalation point for Snowflake, Talend, data integration issues during U.S. business hours.
• Lead investigations and root-cause analysis for data availability, quality, and pipeline reliability issues.
• Identify recurring issues and engineer long-term solutions to reduce manual intervention.
• Drive improvements in platform reliability, observability, and automation.
• Contribute to Data Engineering and Analytics initiatives involving Snowflake, Talend, and cloud technologies.
• Build understanding of end-to-end data ecosystem including source systems and analytics platforms.

Skills

SQL

Snowflake

Talend

ETL/ELT

Data pipelines

Data integration

Python

Cloud platforms

Observability

Analytical thinking

Tools

Power BI

Tableau

Qlik

Job description

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

• Hands‑on experience with both Snowflake and Talend.
• Experience with Python or other scripting/programming languages used for data engineering and automation.
• Experience with AWS, Azure, or other cloud platforms.
• Exposure to Qlik, Power BI, Tableau, or other enterprise analytics platforms.
• Experience with monitoring, observability, data quality, or DataOps technologies.
• Exposure to Generative AI, AI agents, machine learning, or AI‑assisted engineering tools.
• Experience automating technical or operational processes.
• Experience working in pharmaceutical, life sciences, healthcare, or another large enterprise environment.
• Experience working with global onsite/offshore delivery teams.

The Mindset We Value

• Takes ownership of problems and follows them through resolution.
• Is curious about how the entire data ecosystem works, not just one application or technology.
• Enjoys solving difficult technical problems.
• Wants to understand the business impact behind technical issues.
• Looks for opportunities to automate rather than repeatedly perform manual work.
• Is excited about learning Snowflake, Talend, cloud, AI, and emerging data technologies.
• Communicates proactively and collaborates effectively across teams.
• Wants to grow into broader technical and leadership responsibilities.

Innovation & AI-Enabled DataOps

Our vision is to continuously evolve traditional data operations toward a more proactive, automated, and intelligent DataOps model.

The successful candidate will have the opportunity to contribute to this transformation by exploring and implementing practical uses of automation and AI to:

• Detect potential data and platform issues earlier.
• Accelerate technical troubleshooting and root‑cause analysis.
• Automate repetitive operational activities.
• Improve data‑quality monitoring and anomaly detection.
• Make operational knowledge and troubleshooting information easier to access.
• Improve engineering productivity and platform reliability.

AI experience is not required. We are looking for someone who has the curiosity and technical foundation to learn and apply these technologies to real enterprise problems.

Career Growth

This position is designed to provide significant technical and professional growth.

You will work closely with experienced Data Engineering leaders while progressively building expertise across Snowflake, Talend, enterprise data architecture, cloud technologies, DataOps, automation, analytics, and AI.

As your technical, platform, and business knowledge grows, you will have opportunities to:

• Become a key technical owner for enterprise data platforms.
• Lead technical workstreams and smaller data engineering projects.
• Participate in architecture and solution‑design decisions.
• Mentor other engineers.
• Contribute to DataOps and AI modernization initiatives.
• Progress into a Senior Data Engineer / Technical Lead role.
• Develop toward broader Data Engineering leadership and backup technical leadership responsibilities.

Why This Role

It is an opportunity to own and improve enterprise data platforms, solve meaningful technical problems, work on new engineering initiatives, modernize operations through automation and AI, and develop toward technical leadership.