At Resilinc, our mission is to make supply chains more resilient through visibility, AI-powered monitoring, and predictive analytics. Our platform is trusted by leading global enterprises to anticipate, assess, and respond to supply chain disruptions.
We are looking for a Senior Data Engineer who combines expertise in modern data platforms with strong customer engagement skills. This role operates at the intersection of Data Engineering, Product, Engineering, and Customer Success, partnering directly with enterprise customers to design, build, and scale data solutions that power business-critical applications and analytics.
What You'll Do
- Partner directly with enterprise customers and business stakeholders to understand data challenges, define requirements, and deliver scalable solutions.
- Own technical delivery for customer engagements from discovery and solution design through implementation and adoption.
- Help customers maximize the value of Resilinc’s data and analytics capabilities through effective solution design and execution.
- Present technical architectures, implementation plans, and business outcomes to both technical and executive audiences.
- Design, build, and maintain scalable batch and real-time data pipelines and data products using Databricks, ClickHouse, Python, and distributed data processing frameworks.
- Architect modern cloud-native data platforms leveraging Databricks, Delta Lake, Azure Data Services, and distributed processing technologies.
- Develop robust ETL/ELT frameworks, data models, and data quality monitoring processes.
- Optimize data storage, query performance, scalability, reliability, and cost efficiency across large-scale datasets.
- Build and maintain data products that enable analytics, reporting, operational workflows, and AI/ML applications.
- Collaborate closely with Product, Engineering, Solutions Consulting, and Customer Success teams to deliver customer outcomes.
- Drive best practices in data governance, security, observability, reliability, and operational excellence.
- Contribute to architecture decisions, technical design reviews, and platform evolution.
- Mentor junior engineers and contribute to engineering best practices.
Customer Engagement & Solution Ownership
Data Platform & Pipeline Engineering
Engineering Leadership & Collaboration
What You'll Bring
- BE/MS in Computer Science, Information Technology, Engineering, or a related field.
- 5+ years of experience in data engineering, data platform development, or related disciplines.
- Strong experience with Databricks, Apache Spark, Delta Lake, or similar distributed data processing technologies.
- Experience with cloud-based data platforms and services, including Azure (preferred) or equivalent cloud ecosystems.
- Experience designing and operating analytical data platforms using ClickHouse or similar high-performance analytical databases.
- Advanced proficiency in Python and SQL, with strong software engineering fundamentals.
- Experience building scalable ETL/ELT pipelines, orchestration workflows, and modern data architectures.
- Strong understanding of data modeling, data warehousing, and analytics platform design.
- Experience implementing CI/CD, infrastructure automation, and DevOps practices for data platforms.
- Excellent communication and stakeholder management skills, with the ability to translate business requirements into technical solutions.
- Ability to navigate ambiguity, drive outcomes independently, and succeed in customer-facing environments.
Core Qualifications
What Will Make You Stand Out
- Experience in a Forward Deployed Engineer (FDE), Solutions Engineer, Solutions Architect, Technical Consultant, or customer-facing engineering role.
- Experience working with Supply Chain, Logistics, Manufacturing, or Enterprise SaaS platforms.
- Familiarity with data governance, lineage, metadata management, and data catalog solutions.
- Experience with Infrastructure as Code tools such as Terraform.
- Exposure to AI/ML platforms, feature engineering pipelines, and data infrastructure supporting Generative AI applications.
- Experience designing and operating real-time data processing systems and streaming architectures.
- Demonstrated ability to mentor engineers and lead technical initiatives across teams.
Skills Required
- BE/MS in Computer Science, Information Technology, Engineering, or related field
- 5+ years of experience in data engineering or data platform development
- Strong experience with Databricks and distributed data processing (Apache Spark)
- Experience with Delta Lake and modern data lake architectures
- Experience designing and operating analytical platforms using ClickHouse or similar
- Advanced proficiency in Python
- Advanced proficiency in SQL
- Experience building scalable ETL/ELT pipelines and orchestration workflows
- Experience with cloud-based data platforms and services (Azure preferred)
- Experience implementing CI/CD, infrastructure automation, and DevOps practices for data platforms
- Excellent communication and stakeholder management skills; customer-facing experience
- Ability to work independently, navigate ambiguity, and drive outcomes
- Experience in Forward Deployed Engineering, Solutions Engineering, Solutions Architecture, or technical consulting
- Experience with Supply Chain, Logistics, Manufacturing, or Enterprise SaaS platforms
- Familiarity with data governance, lineage, metadata management, and data catalog solutions
- Experience with Infrastructure as Code tools such as Terraform
- Exposure to AI/ML platforms, feature engineering pipelines, and data infrastructure for Generative AI
- Experience designing and operating real-time data processing systems and streaming architectures
- Demonstrated ability to mentor engineers and lead cross-team technical initiatives
What We Do
Every year, tens of thousands of events – ranging from natural disasters to factory fires to health epidemics – shut down manufacturing and wreak havoc on global supply chains. We believe a resilient supply chain is good for everyone: it keeps product flowing, the world moving, and most importantly, people in their jobs. Resilinc was founded with the purpose of strengthening global supply chains, making them resilient, sustainable, transparent, and secure. We do this via our technology-driven solutions, which create an ecosystem where organizations can collaborate with their suppliers and customers with a spirit of transparency and trust to acquire unmatched visibility into their multi-tier supply networks, and partner across tiers seamlessly to recover supply chains during disruptions. Since our launch in 2010, Resilinc has defined the supply chain mapping, monitoring, and resiliency space and is widely considered the gold standard for supply chain resiliency, worldwide. With over 1 million supplier sites mapped encompassing over 4 million parts and raw materials, we are the first line of defense for our customers, helping them navigate supply disruptions. Our early-warning alert system monitors and predicts potential disruptions across suppliers, sites, and materials; our platform enables them to collaborate closely with their suppliers; our historical data-backed insights give them options on appropriate actions to take. Always innovating, our AI-powered predictive solutions can predict delivery delays, price movements, and supply constraints for raw materials and commodities before they happen. Resilinc helps our customers protect revenue and turn supply chain risks into opportunities to gain a competitive advantage
.jpg)
