Manila, NCR, City of Manila
20 hours ago
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.

 

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