Data Architect

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November 4

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Innowhyte Inc

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Artificial Intelligence • B2B • Enterprise

Innowhyte Inc is an enterprise-focused innovation consultancy and AI services provider that combines data and intelligence with design thinking to build enterprise-scale solutions. The company emphasizes Pattern-Oriented Innovation and an a7i framework to templatize repeatable innovation patterns, accelerate time-to-market, and harness opportunities in unmet "white space" areas across business domains. Innowhyte works with organizations to uncover the right problems, convert insights into actionable solutions, and harden designs for scale and sustainable impact.

11 - 50 employees

🤖 Artificial Intelligence

🤝 B2B

🏢 Enterprise

📋 Description

• Design, develop, and maintain robust and scalable data pipelines to support analytics and machine learning applications. • Collaborate with cross-functional teams, including data scientists and software engineers, to implement data-driven solutions. • Optimize and manage data storage systems and ensure high availability, reliability, and performance. • Design, develop, and maintain robust and scalable ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) data pipelines to support analytics and machine learning applications. • Ensure data pipelines are optimized for efficiency, reliability, and scalability, handling both structured and unstructured data seamlessly. • Handle large-scale datasets, ensuring data integrity and consistency across platforms. • Provide technical expertise and mentorship to junior engineers and stakeholders. • Implement best practices in data engineering, including version control, testing, and deployment. • Stay updated with emerging technologies and tools in data engineering, AI/ML, and cloud ecosystems.

🎯 Requirements

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. • Minimum 5+ years of hands-on experience in data engineering or related roles. • Proficiency in Python programming and its data-processing libraries (e.g., Pandas, PySpark). • Proven expertise in handling large-scale data systems such as distributed databases, data warehouses, and data lakes. • Strong experience with cloud platforms (AWS, Azure, or GCP) and associated tools for data storage, processing, and orchestration. • Practical knowledge of data pipeline frameworks like Apache Airflow, Kafka, or Spark. • Hands-on technical expertise in designing and implementing end-to-end data solutions. • Familiarity with Generative AI (GenAI) and AI/ML technologies.

🏖️ Benefits

• Enjoy the flexibility to work from the comfort of your home, with no commute hassles. • Work directly with the CXO team, gaining valuable insights and contributing to strategic decisions. • Take the opportunity to initiate, own, and drive impactful data engineering projects across the organization. • Become a key member of the engineering leadership team, driving innovation and excellence within the data domain. • Work with state-of-the-art technologies in AI, ML, and data engineering. • Competitive compensation and ample opportunities for career growth.