Lead the design and implementation of enterprise-scale cloud data platforms for a global AI and digital transformation solutions provider. Drive scalable data architectures, cloud migrations, and AI-ready data ecosystems while mentoring engineering teams. Requires 3+ years of experience in cloud data engineering, distributed systems, and cross-functional collaboration.
Key Highlights
Technical leadership in designing and optimizing cloud-based data platforms (AWS, Azure, GCP, Databricks, Snowflake)
Leadership in cloud migration initiatives and evaluation of emerging technologies for AI/ML workloads
Mentorship of junior engineers and cross-functional collaboration with data scientists, architects, and stakeholders
Key Responsibilities
Design and implement scalable cloud-based data platforms using AWS, Azure, GCP, Databricks, and Snowflake
Lead enterprise data platform architecture, data warehouse, and data lake implementation projects
Develop and optimize large-scale distributed data processing pipelines using Spark and Python
Evaluate emerging technologies and conduct Proof of Concept (PoC) activities for AI/ML and analytics workloads
Collaborate with cross-functional teams to ensure data quality, security, governance, and platform reliability
Mentor junior engineers and provide technical leadership throughout the project lifecycle
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Technical Skills Required
Amazon Web Services / Microsoft Azure / Google Cloud Platform
Distributed Data Processing (Spark, Python)
Data Warehousing & Data Lake Architecture
Benefits & Perks
Visa sponsorship encouraged
Relocation assistance offered
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Nice to Have
Experience with AI or Generative AI to improve software development workflows
Cloud certifications (AWS, Azure, GCP, Snowflake, or Databricks)
Knowledge of data governance, data quality, metadata management, and cloud security best practices
Job Description
Our client is a global technology solutions provider specializing in Artificial Intelligence (AI), Cloud Computing, Data Engineering, and Digital Transformation (DX). The organization partners with enterprise clients across multiple industries to design, modernize, and optimize large-scale cloud data platforms that support advanced analytics, AI initiatives, and business intelligence.As demand for enterprise data modernization continues to grow, the company is expanding its Data Engineering practice to deliver next-generation cloud data architectures, scalable analytics platforms, and AI-ready data ecosystems using leading cloud technologies and modern data platforms.
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