Senior Data Engineer

Responsibilities: <ul><li>Develop and implement accurate forecasting models to predict product demand using historical data.</li><li>Leverage time series analysis techniques to generate business insights and drive data-driven decisions.</li><li>Continuously optimize forecasting models to adapt to changing business needs and improve forecast accuracy.</li><li>Apply advanced ML algorithms (e.g., XGBoost, Random Forest, Deep Learning) to solve complex business problems.</li><li>Conduct exploratory data analysis (EDA) to uncover trends, anomalies, and actionable insights.</li><li>Develop and validate machine learning models to support various analytical use cases.</li><li>Design scalable and maintainable data pipelines and architectures to support analytical workflows.</li><li>Ensure high data quality and consistency across multiple data sources.</li><li>Collaborate with engineering teams to implement best practices in data storage, processing, and governance.</li><li>Build and deploy data solutions on Databricks, leveraging its ML and Spark capabilities.</li><li>Utilize AWS services (e.g., S3, EC2, Lambda, SageMaker) for scalable cloud-based model training and deployment.</li><li>Ensure cost-effective and optimized use of cloud resources in project implementations.</li><li>Design end-to-end analytics and ML solutions tailored to client needs.</li><li>Lead technical discussions and contribute to solution architecture.</li><li>Translate business requirements into technical specifications and deliver actionable results.</li><li>Understand key metrics and pain points within manufacturing and supply chain operations.</li><li>Use domain knowledge to frame problems accurately and drive impactful analytical outcomes.</li><li>Collaborate with stakeholders to ensure alignment between analytics and business goals.</li><li>Understand SAP modules related to supply chain and manufacturing (e.g., MM, PP, SD) Use SAP knowledge to enhance data modeling and business context understanding.</li></ul> Requirement: <ul><li>Skills Required: o Strong proficiency in Python o Expertise in Time Series Forecasting and Demand Forecasting o Familiarity with Advanced ML Algorithms and Data Analysis o Must have experience in Data Architecture – practical exposure required o Hands-on experience with Databricks and AWS (should be visible in past projects) o Design and solutioning experience highly valued</li><li>Strong background in data architecture, solution design, and end-to-end ML model lifecycle</li><li>Experience as Data Architect, Solution Architect, or in equivalent architectural roles</li><li>Should come from a product-based or data engineering-focused startup background</li></ul>

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