Data Engineer

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.