Overview / Job Summary

We are seeking experienced AI & Data Consultants to join our growing team supporting enterprise-scale Data, Analytics, and Artificial Intelligence initiatives. This opportunity covers multiple specialization tracks, including Machine Learning Engineer, AI System Analyst, and Data Engineer, and is ideal for professionals who possess strong expertise in data platforms, AI/ML technologies, enterprise analytics, and large-scale data processing environments.

Successful candidates will contribute to the design, development, implementation, and optimization of enterprise data and AI solutions, working closely with business stakeholders, data scientists, architects, and engineering teams. Depending on project requirements, consultants may focus on data engineering, machine learning operationalization, AI/NLP solution design, data architecture, or enterprise analytics platforms.

Job Roles & Responsibilities

Depending on project assignment and specialization, responsibilities may include:

• Design, develop, and maintain enterprise data platforms, data pipelines, and AI-enabled solutions.
• Build and optimize batch and real-time data processing systems using modern big data technologies and distributed computing frameworks.
• Design and implement scalable data architectures across Data Lake, Data Warehouse, and enterprise analytics environments.
• Develop data ingestion, transformation, and orchestration frameworks to support business intelligence, reporting, analytics, and AI initiatives.
• Collaborate with business stakeholders to gather, analyze, and translate business and regulatory requirements into technical solutions.
• Design AI and NLP-driven use cases such as text classification, entity extraction, risk identification, document processing, and intelligent summarization.
• Support the deployment, operationalization, monitoring, and optimization of machine learning models within enterprise environments.
• Perform data validation, testing reviews, solution assessments, and performance optimization activities.
• Ensure adherence to data governance, security, compliance, and enterprise architecture standards.
• Participate in solution design, technical architecture discussions, project estimation, and delivery planning.
• Work closely with cross-functional teams including Data Scientists, Data Engineers, Business Analysts, Architects, and Product Owners to deliver scalable and reliable solutions.

Job Qualifications & Requirements

• Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, Mathematics, or a related field.
• Minimum 6+ years of relevant experience in Data Engineering, Machine Learning Engineering, AI Analytics, Data Architecture, or related disciplines.
• Strong proficiency in one or more programming languages such as Python, Java, or SQL.
• Experience working with enterprise data platforms, data warehouses, data lakes, and large-scale analytics environments.
• Hands-on experience with Big Data technologies such as Spark, Kafka, Hive, Iceberg, Flink, NiFi, Trino, Impala, or similar technologies.
• Experience designing and developing ETL/ELT pipelines, data ingestion frameworks, and data transformation processes.
• Understanding of machine learning concepts, model deployment, operationalization, and AI-enabled analytics solutions.
• Experience with NLP-related use cases, AI-driven analytics, or unstructured data processing is an advantage.
• Knowledge of data architecture, data governance, metadata management, and enterprise data management practices.
• Familiarity with machine learning frameworks and tools such as Cloudera Machine Learning (CML), Spark MLlib, Scikit-learn, XGBoost, or equivalent platforms is beneficial.
• Experience with performance tuning, optimization, troubleshooting, and production support of enterprise data applications.
• Strong analytical, problem-solving, and communication skills.
• Ability to engage effectively with both technical teams and business stakeholders.
• Experience working in Agile delivery environments.

Technologies & Domains May Include

• Python, Java, SQL, Shell Scripting
• Apache Spark, Kafka, Flink, Hive, NiFi, Iceberg, Trino, Impala
• Teradata, Informatica PowerCenter, Data Warehouse & Data Lake Platforms
• Cloudera Machine Learning (CML), Spark MLlib, Scikit-learn, XGBoost
• Data Governance Tools (Ranger, Atlas)
• NLP, AI Analytics, Machine Learning Operations (MLOps)
• Real-Time Data Processing and Streaming Architectures
• Enterprise Data Architecture, Data Governance, and Regulatory Analytics

This role offers the opportunity to work on cutting-edge AI, Machine Learning, Data Engineering, and Enterprise Analytics projects across diverse industries, helping organizations unlock value from their data and accelerate their digital transformation initiatives.

For questions/clarifications and direct applications, kindly send us an email attached your latest and updated CV to queenie.antioquia@geco.asia.