LeanDNA is helping solve the $150B problem that global manufacturers face–excess inventory tying up critical working capital and keeping manufacturing companies from being as efficient as they need to be. Without an effective way to optimize inventory, manufacturers are buying too much, too little, or placing inventory in the wrong place at the wrong time. Companies are stuck fighting operational fires related to critical inventory shortages, creating delays in delivering their product to customers on time.

LeanDNA's factory inventory optimization and shortage management solution quickly empowers supply chain professionals to dramatically reduce excess inventory, deliver on time, and establish operational command of their organization’s inventory operations. LeanDNA optimizes the inventory management process by adding the much-needed (and much-appreciated) artificial intelligence into the forgotten area of the business: The factory. It’s not just about smart inventory planning—true optimization occurs when procurement leaders have command over the operation, and the supply chain teams tasked with bringing those plans to life have total visibility, AI-driven recommendations, and a clear game plan for hitting their inventory goals every time.

The Senior Data Integration team at LeanDNA is responsible for integrating customer data with the LeanDNA cloud solution. Senior Data Integration Engineers ensure we are getting high quality and current data from the source systems, and that this data is reliably uploaded to the cloud in a uniform format that can be consumed by the LeanDNA analytics and reporting engines. This role is essential in helping LeanDNA customers quickly and successfully utilize our cloud-based Supply Chain Analytics solution to drive results for their businesses.

The ideal candidate would possess several skill sets including proficiency with data technologies and SQL, passion for data analytics, and excellent communication skills. You will be working alongside (and at times, onsite) with customer IT staff and business analysts to retrieve customer data and understand the customer’s data structures and semantics. You will use your data analytics and SQL capabilities to transform the data and upload it to the LeanDNA cloud solution. You will be working with the LeanDNA Customer Success team to ensure that the data is of the highest possible quality, and with the LeanDNA Engineering team to integrate into the LeanDNA data pipeline. This is a fantastic role for a data geek with awesome skills for someone that wants to jump into an extremely fast-cycle deployment world. Your energy and enthusiasm to work and grow alongside our high-trajectory team are essential!

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Responsibilities:**

Perform initial data integration with new customers, and maintain the data extraction and transformation processes
Build and maintain processes to extract data from various sources, transform it into a usable format, and load it into databases / data lakes
Automate workflows and improve existing processes for better performance and efficiency
Integrate data from systems such as APIs, databases, ERPs web services, third-party platforms, and more
Manage data quality by identifying and resolving data issues, ensuring consistency, completeness, and accuracy
Act as the primary technical point of contact for a group of customers
Analyze customer data to ensure accuracy and to help the customer achieve their goals (inventory reduction, shortage prevention)

Required Skills:

Proficiency in languages like Python, Java or SQL
Experience with relational and NoSQL databases
Experience with cloud data infrastructure on AWS or Azure
Collaborate effectively with cross-functional teams, including software engineers, customer success and product managers
Continuously monitor and improve the data pipeline to ensure efficiency and reusability

Qualifications:

The following qualifications will contribute significantly to the success of a Senior Data Integration Engineer in LeanDNA:

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field
Previous experience in a data engineering role or a related position involving data management, extraction and analysis
Ability to learn systems and business processes quickly
Experience with ERP systems and other business systems
Advanced SQL skills
Proficiency with data pipeline engineering
Strong understanding of data design principles
Ability to explain technical concepts to non-technical stakeholders

Preferred Qualifications: