Data Engineer

Data Engineering & Data Platform Consultant

• Head Count hiring: 3
• Work Set up: Hybrid (Onsite in Taguig, BGC)
• Work Schedule: M-F with possible on-call schedules, Morning Shift – Oceania UTC and Holiday applies
• Level: Mid to Senior , 2 – 5 Years or up experience 

In this role, you will design and develop state-of-the-art Data Platforms that enable Advanced Analytics and AI, driving tangible business outcomes for our clients.

Key Responsibilities

• Consulting: Engage with clients to understand their needs, define strategy, and translate business requirements into technical solutions.
• Azure Data Integration: Implement and manage data integration solutions using Azure tools.
• Design & Architecture: Architect, model, and integrate data solutions that align with business goals and best practices.
• Development:  Build and maintain Lakehouse, Data Lake, and Data Warehouse solutions.
• Agile/Scrum Participation:  Collaborate effectively in Agile/Scrum teams to deliver high-quality solutions.

Required Skills

• Azure Cloud Expertise: Proficiency in Azure cloud services, particularly in data engineering and integration.
• Azure Data Factory/Data Pipelines:  Hands-on experience with Azure Data Factory for data movement and transformation.
• Azure Synapse/Azure SQL:  Strong knowledge of Azure Synapse and SQL databases.
• Azure Databricks or Spark: Experience in leveraging Azure Databricks or Spark for big data processing.
• Data Modelling & Integration:  Solid understanding of data modeling and integration techniques.
• SQL: Advanced SQL skills for querying and managing data.
• Python/PySpark: Proficiency in Python and PySpark for data processing.
• Technical Excellence: A strong technical foundation to maximize the value of underlying technologies.
• Agile Methodology: Experience in delivering projects using Agile methodologies.

Preferred Skills

• Net Development: Familiarity with .Net for data applications.
• API Development: Experience in developing APIs for data integration.
• IoT & Stream Analytics: Knowledge of IoT data ingestion and real-time stream analytics.
• Power BI: Proficiency in Power BI for data visualization.