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Sr. Data Engineer

Overhaul LLC

Senior Data EngineerOverhaul is a supply chain integrity solutions company that allows shippers to connect disparate sources of data into the first fully transparent situational analysis engine designed for the logistics industry. Data that is transformed into critical insights can instantly trigger corrective actions, impacting everything from temperature control to handling requirements or package-level tracking, ensuring cargo arrives at its destination safely, undamaged, and on time. We are a dynamic, innovative, and fun team who is highly committed to our customers' experiences and our Mission and Vision.We are seeking an experienced and passionate Senior Data Engineer to join our Data Platform team. You will be joining a small team responsible for architecting, building, and maintaining the scalable, enterprise-grade data systems that power our data products and capabilities. You'll straddle the worlds of DataOps, MLOps, and Infrastructure, enabling both the next generation of analytics functionality and an AI Platform to fuel our AI-driven product innovation.Since data engineers are responsible for their pipelines at Over-haul, this role requires engineers to take ownership of the operational excellence in their domain. In addition, the ideal candidate will have excellent data intuition and share our passion for continuously improving how we handle streaming data at Over-haul.This position is based in Austin, Texas, but remote work is available.Who Are You?You have strong product ownership and good intuition on how data is used to drive business decisionsYou strive to write elegant code and are comfortable with independently picking up new technologies.You have mastery over Python programming language and SQL.You enjoy helping teams push the boundaries of analytical insights, creating new product features using data, and powering machine-learning models.You have a strong background in at least one of the following: distributed data processing or software engineering of data services.You are familiar with big data technologies like Spark and comfortable working with web-scale datasets.You are passionate about the end-to-end software development lifecycle, focusing on automation, testing, CI/CD, and documentation.You have an eye for detail, good data intuition, and a passion for data quality.You love working independently while also collaborating and giving/receiving candid feedback.You are comfortable working in a rapidly changing environment with ambiguous requirements. You are nimble and take intelligent risks.Job DutiesDesign and maintain streaming data pipelines using Databricks, and SparkCreate ML Pipelines to feed data and update a variety of models.Develop ML models to enhance predictive analytics capabilities and support decision-making processes across various departments.Work ExperienceExperience with Cloud based Data Lake ToolsExperience with designing and implementing data pipelinesPython and SparkSQL/Spark experiencePlusesAzure Data Tools, such as Data Lake, Synapse, or FabricPower BI ExperienceCertifications and EducationBS in Computer Science or Related field preferred, but not requiredPerks and BenefitsTop employee health and well-being benefitsCare giver/adoption/family leaveFlexible Time Off PolicyCasual dressPerks and discounts through employee assistance programDiversity and Inclusivity StatementOverhaul has always been, and always will be, committed to diversity and inclusion. Our Overhaul Culture Code's top listed commitment is to "Diversity and Synergy." All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law. We strongly encourage people from underrepresented groups to apply!

Vacancy posted 12 hours ago
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