Senior Data Engineer

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

Customer Engagement & Solution Ownership

• 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.

Data Platform & Pipeline Engineering

• 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.

Engineering Leadership & Collaboration

• 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.

What You'll Bring

Core Qualifications

• 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.

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.