Senior Data Engineer

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Resilinc

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2010

🏢 Enterprise

☁️ SaaS

Enterprise • AI • SaaS

Resilinc is a leading provider of supply chain risk management and resiliency solutions. The company uses advanced technologies such as AI for mapping, monitoring, and predictive analytics to offer deep supply chain visibility and risk scoring. With their proprietary data, Resilinc helps businesses ensure continuity by forecasting disruptions and collaborating effectively with global suppliers. They serve industries including aerospace, healthcare, and high-tech manufacturing, providing tools for compliance, business continuity planning, and ESG adherence. Their services cater to various business roles including CEO, CPO, and supply chain resiliency managers.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Full-stack benefits for health, wealth and wellbeing