Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI.Key ResponsibilitiesArchitectural Leadership: Lead the design of high-level data architectures in Multi-Cloud environments (Azure and GCP) specifically for IIoT (Industrial Internet of Things) and manufacturing execution systems.Industrial Data Modernization: Oversee the migration of legacy factory data systems to unified storage platforms like Hadoop and Databricks.Smart Manufacturing Insights: Build visualization frameworks in Tableau to track OEE (Overall Equipment Effectiveness), supply chain bottlenecks, and production quality metrics.Predictive Analytics: Utilize Spark, PySpark, and Python to develop models for predictive maintenance and demand forecasting.End-to-End Delivery: Manage the full SDLC for high-impact projects, ensuring data integrity and security across global manufacturing sites.Strategic Mentorship: Guide technical teams across onshore and offshore models, fostering excellence in data engineering and industrial AI.RequirementsManufacturing Domain Expertise: Proven experience applying data solutions to manufacturing challenges, such as inventory optimization, shop-floor automation, or digital twins.Extensive IT Background: Over 18+ years of experience with a strong focus on Big Data ecosystems including Hadoop, Hive, and Spark.Cloud Mastery: Deep expertise in Azure and GCP , supported by certifications in Data Engineering and Architecture.Technical Depth: Hands-on proficiency with Informatica , Kubernetes , and advanced SQL for complex data exploration.Education: A Master’s Degree in Software Engineering.Analytical Skills: Strong data processing and ETL experience using Python (NumPy/Pandas).BenefitsSignificant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI.
Key Responsibilities
- Architectural Leadership: Lead the design of high-level data architectures in Multi-Cloud environments (Azure and GCP) specifically for IIoT (Industrial Internet of Things) and manufacturing execution systems.
- Industrial Data Modernization: Oversee the migration of legacy factory data systems to unified storage platforms like Hadoop and Databricks.
- Smart Manufacturing Insights: Build visualization frameworks in Tableau to track OEE (Overall Equipment Effectiveness), supply chain bottlenecks, and production quality metrics.
- Predictive Analytics: Utilize Spark, PySpark, and Python to develop models for predictive maintenance and demand forecasting.
- End-to-End Delivery: Manage the full SDLC for high-impact projects, ensuring data integrity and security across global manufacturing sites.
- Strategic Mentorship: Guide technical teams across onshore and offshore models, fostering excellence in data engineering and industrial AI.
Requirements
- Manufacturing Domain Expertise: Proven experience applying data solutions to manufacturing challenges, such as inventory optimization, shop-floor automation, or digital twins.
- Extensive IT Background: Over 18+ years of experience with a strong focus on Big Data ecosystems including Hadoop, Hive, and Spark.
- Cloud Mastery: Deep expertise in Azure and GCP , supported by certifications in Data Engineering and Architecture.
- Technical Depth: Hands-on proficiency with Informatica , Kubernetes , and advanced SQL for complex data exploration.
- Education: A Master’s Degree in Software Engineering.
- Analytical Skills: Strong data processing and ETL experience using Python (NumPy/Pandas).
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
