Data Engineer

Manila, NCR, City of Manila, 1st district, Philippines

Full Time Mid-level / Intermediate USD 49K - 91K *

Fujitsu

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Posted 1 week ago

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.