Chief Data Architect for Supply Chain Innovation
1 week ago
About Verticalmove, Inc
Verticalmove, Inc is a rapidly growing company revolutionizing the supply chain planning industry with its AI-driven demand planning and inventory replenishment software. With a total addressable market (TAM) of $28.9 billion in 2023, projected to reach $45.2 billion by 2027 at a compound annual growth rate (CAGR) of 9.4%, the company targets small and medium-sized businesses (SMBs), providing technological advantages previously exclusive to large enterprises.
Job Description
We are seeking a highly skilled Chief Data Architect to design, implement, and deploy our next-generation data platform tightly integrated with Amazon AWS services such as EMR, Athena, Glue, and Spark. This role involves developing an ultra-real-time, AI-driven demand planning engine to help us serve industries managing perishable items, including food manufacturing, restaurants, grocery stores, pharmaceuticals, and more.
Key Responsibilities
- Design and build a scalable, fault-tolerant data platform optimized for distributed computing and large-scale data processing using AWS, Databricks, and Apache Spark.
- Implement data pipelines and ETL/ELT processes to efficiently ingest, transform, and load massive datasets from various sources.
- Leverage cloud data platforms to enable seamless data sharing, near-zero maintenance, and fast analytics on both structured and semi-structured data.
- Build and optimize distributed computing jobs and queries to ensure maximum performance, cost efficiency, and scalability by distributing tasks to the lowest level possible.
- Collaborate with data scientists, machine learning engineers, and software developers to build solutions that power GenAI applications.
- Provide guidance on distributed computing architecture and mentor junior data engineers.
- Implement data governance, security, and compliance best practices.
- Drive innovation by partnering with global teams to enhance supply chain technology.
Requirements
- A Bachelor's or Master's degree in Data Science, Computer Science, Operations Research, Statistics, or a related field.
- 5+ years of experience as a Data Engineer, with strong expertise in big data technologies.
- 7+ years of experience with cloud architecture, with extensive expertise in AWS.
- Strong proficiency in SQL, Python, and data modeling techniques.
- Deep knowledge of distributed computing principles and frameworks, including experience with data streaming (Kafka).
- Hands-on experience with developing and deploying distributed computing applications using cloud-based platforms (e.g., AWS EMR, Azure HDInsight).
- Experience with cloud data platform architectures and best practices for ETL/ELT, data sharing, and query optimization.
- Experience in building and optimizing distributed computing frameworks to handle functional business logic and achieve scalability.
- AWS, GCP, or Azure certifications are highly valued.
Salary
The estimated salary for this position is between $180,000 - $250,000 per annum, depending on experience and location.
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