Yondu is a Philippine-based IT solutions company owned by Globe Telecom. We empower businesses across various industries through a wide array of innovative technology solutions to help them scale in the new digital economy. Our mission is to create happier technological experiences by turning great ideas into excellent and valuable business solutions.
If you’re looking to advance your career in the IT industry, Yondu is the best place to be. You will be a part of a young, dynamic culture that always pursues innovation and growth. As a Yondude, you’ll gain fresh perspectives from a team of knowledgeable and competitive individuals and learn how to develop cutting-edge business solutions that go above and beyond. You’ll also enjoy collaborating with brilliant and fun people who are ready to take on the world.
Established in 2001, our company has grown exponentially, and we’re always on the lookout for highly skilled and competitive individuals to innovate and evolve with. If this sounds exciting for you, #BeAYondude, and leverage your expertise to help us achieve our ultimate goal of going above and beyond!
Join us and grow your career in the IT industry!

YONDU INC.

What you'll be doing:

Designing, building, and maintaining scalable and efficient data pipelines to extract, transform, and load data from various sources

Developing and optimising data models to support business intelligence and advanced analytics

Collaborating with cross-functional teams to understand and address business requirements

Automating data-related processes and workflows to improve data quality and reduce manual interventions

Continuously monitoring and optimising data systems to ensure reliability, performance, and security

Providing technical expertise and guidance to support the implementation of data-driven solutions

Data Engineer

<ul>
	<li>Experience collecting, organizing, analyzing, and disseminating abundant information with accuracy</li>
	<li>Develop and implement advanced data analysis techniques to optimize efficiency and quality.</li>
	<li>Prepare and present detailed reports, dashboards, and visualizations of operational results for stakeholders.</li>
	<li>Interpret data using analytics and statistical methods, providing insights and recommendations.</li>
	<li>Lead the full lifecycle of analytics projects, from requirements gathering to design and execution.</li>
	<li>Evaluate key performance indicators and provide ongoing reports to support decision-making.</li>
	<li>Collaborate with cross-functional teams to ensure data integrity and alignment with business goals.</li>
	<li>Stay updated on industry trends and emerging technologies in data analysis and analytics tools.</li>
	<li>Conducted data quality assessments and implemented improvements as needed.</li>
	<li>Support the development and implementation of data governance policies and procedures.</li>
	<li>Mentor junior analysts and provide training on data analysis techniques and tools.</li>
	<li>Other job-related activities may be assigned from time to time.</li>
</ul>

Data Analyst

<ul>
	<li>Design, build, and maintain scalable, secure data pipelines and storage systems; ensure data quality through ETL processes and regular checks.</li>
	<li>Implement policies and practices to control, optimize, and secure data assets, ensuring data integrity and accessibility.</li>
	<li>Develop and maintain data models, structures, and databases to meet business needs; communicate data architecture effectively.</li>
	<li>Develop, test, and maintain scripts and programs to automate data processing and pipelines, adhering to industry standards.</li>
	<li>Create and operationalize data visualization solutions to simplify complex data for stakeholders and decision-making.</li>
	<li>Work with cross-functional teams to gather data requirements, optimize existing processes, and deliver ad hoc reports and insights</li>
</ul>

<ul>
	<li class="text-justify">
	Design, build, and maintain scalable, secure data pipelines and storage systems; ensure data quality through ETL processes and regular checks.
	</li>
	<li class="text-justify">
	Implement policies and practices to control, optimize, and secure data assets, ensuring data integrity and accessibility.
	</li>
	<li class="text-justify">
	Develop and maintain data models, structures, and databases to meet business needs; communicate data architecture effectively.
	</li>
	<li class="text-justify">
	Develop, test, and maintain scripts and programs to automate data processing and pipelines, adhering to industry standards.
	</li>
	<li class="text-justify">
	Create and operationalize data visualization solutions to simplify complex data for stakeholders and decision-making.
	</li>
	<li class="text-justify">
	Work with cross-functional teams to gather data requirements, optimize existing processes, and deliver ad hoc reports and insights
	</li>
</ul>

Roles and Responsibilities

1. SQL Proficiency for Analytics

○ Writes optimized queries to support BI workloads.

○ Uses window functions, CTEs, and subqueries for analytical transformations.

○ Tunes queries with a focus on speed for dashboards and reporting.

○ Adapts across SQL dialects (PostgreSQL, BigQuery, Snowflake, etc.).

2. Data Modeling G Warehousing

○ Designs star/snowflake schemas for BI use cases.

○ Balances Kimball (analytics-oriented) and Inmon (integration) approaches.

○ Optimizes partitioning and clustering for query efifiiciency (rather than compute efficiency).

3. BI Readiness G Reporting Support

○ Builds curated datasets for BI tools (Looker, Tableau, Power BI).

○ Collaborates with analysts to ensure usability of datasets.

4. Data Quality G Validation

○ Implements automated testing in dbt or similar.

○ Familiarity with observability tools.

○ Ensures trustworthiness of analytics-layer tables.

5. Pipeline Development (Analytics-Focused)

○ Orchestrates workflows with dbt, Airflow, or Fivetran.

○ Manages ELT with emphasis on transfiormation in the warehouse.

6. Governance G Privacy (User-Facing Data)

○ Implements data masking and role-based access control for analysts.

○ Ensures compliance at the analytics layer.

Data Analytics Engineer

Key Responsibilities

Administer, maintain, and support enterprise-level databases including PostgreSQL, MongoDB, MySQL, and Microsoft SQL Server.

Perform database installations, configurations, upgrades, migrations, and patch management.

Monitor database performance and implement optimization and tuning for high availability and scalability.

Ensure data integrity, security, and compliance through robust backup and recovery strategies.

Collaborate with development and infrastructure teams to design efficient database structures and improve query performance.

Automate repetitive DBA tasks using scripts and tools to improve operational efficiency.

Troubleshoot and resolve database issues, ensuring minimal downtime and quick recovery.

Provide mentorship and technical guidance to junior database team members.

Sr Data Administrator

We are seeking a highly skilled Data Modeler / Architect to lead the design and implementation of scalable data models and transformation pipelines using DBT on Google Cloud BigQuery. This role requires strong client-facing communication skills to understand business data deeply and translate it into robust technical solutions.

Data Modeling &amp; Architecture

Design logical and physical data models aligned with business requirements and long-term architecture goals.

Apply modeling styles such as 3NF, dimensional, anchor, and semantic models for cloud data warehouses.

Define entity relationships, derived fields, business constraints, and data validity rules.

Transformation &amp; Implementation

Build and deploy transformation pipelines using DBT (Data Build Tool) integrated with Google Cloud BigQuery.

Optimize table storage, indexing, and partitioning for performance and scalability.

Apply best practices for cost-efficient querying and data access in BigQuery.

Client Engagement &amp; Communication

Collaborate directly with clients to understand their data landscape, business logic, and reporting needs.

Translate business rules into technical specifications and ensure alignment across stakeholders.

Present data models and transformation strategies clearly to both technical and non-technical audiences.

Must have and Good to have skills: SQL, DBT, Data Modeling

Number of years experiences needed: Min of 4 years

If hybrid, provide number of days in a month or week that needs to be in the office: 2x a week – Midshift (2PM to 12AM)

Location (During onsite): Uptown Tower 3, BGC Taguig City

Data Modeler Architect

Job Description:

The Data Engineer is expected to work with the Team in delivering and supporting Data Analytics Requirements. The resource is expected to collaborate with various stakeholders to deliver needed solutions across the organization. Technical expertise is highly expected from the resource to provide solutions and architecture as needed.

Job Requirements:

<ul>
	<li>Must have at least 4-7 years Relevant experience in Data Engineering.</li>
	<li>Development in Azure Data Factory is a priority but experience with Cloud ETL Looks such as AWS Glue or GCP Cloud Data Fusion/Flow is alo considered.</li>
	<li>Python programming skills in Data Analytics/Big Data is a must.</li>
	<li>Cloud Data Engineering skills in Azure (preferred), AWS, and/or GCP is a must.</li>
	<li>Must have experience working in enterprise environment with Data Warehouse/Data Lake/Data Lakehouse environment.</li>
	<li>Modern Data Architecture and Data Modeling experience.</li>
	<li>Worked on at least 2 enterprise scale projects as a Data Engineer.</li>
	<li>PowerBI or knowledge on BI tools is a must.</li>
	<li>Good communication and writing skills.</li>
	<li>Ability to manage stakeholders.</li>
	<li>Independent can work on his/her own with minimal to zero supervision.</li>
	<li>Machine Learning/AI understanding is nice to have.</li>
</ul>

Senior Data Engineer

Knowledge of reporting and visualization tools such as Business Objects, PowerBI and Tableau.

• Programming Skills – knowledge of database query languages like SQL and Python

 

Solid understanding of data engineering practices, ETL processes, and data warehousing concepts and familiarity with Azure data platforms.

• Proven experience in data analysis and report/dashboard creation using SQL, Python, MS Excel, and Power-BI.

• Strong problem-solving skills with a focus on deriving

actionable insights from complex datasets.

• Excellent communication and collaboration skills.

• Ability to work independently and as part of a team.

• Attention to details.

 

Excellent organizational skills

 

• Strong mathematical and numeracy skills

• Critical Thinking skills

• Excellent communication (verbal and written)

• Ability to work in an open culture with a positive

approach.

Senior Data Analyst

Azure Data Engineer

Responsible for designing, developing, and optimizing big data solutions using the Databricks platform. This role involves close collaboration with data engineers, data scientists, and stakeholders to ensure efficient data processing, quality, and performance 
Key Responsibilities 
• Develop and implement advanced data solutions on Databricks using Python, Scala, or SQL. 
• Optimize ETL processes and data pipelines for performance and reliability. 
• Integrate Databricks notebooks with tools like Azure Data Factory and Synapse Analytics 
• Implement secret scopes and secure data access using Databricks CLI and Azure Service Principals. 
• Collaborate with cross-functional teams to understand data requirements and deliver scalable solutions. 
• Conduct performance tuning and troubleshoot data workflows. 
• Document processes and maintain high standards of code quality and maintainability. 
Qualifications 
• 5+ years of experience in data engineering or similar roles. 
• Strong proficiency in Databricks, Apache Spark, and cloud platforms (Azure). 
• Experience with data modeling, data cleansing, and warehousing at scale (1TB+). 
• Familiarity with Agile delivery paradigms and software engineering best practices. 
• Knowledge of core Python libraries (NumPy, Pandas, Matplotlib) is a plus 
Skills 
• Databricks, Apache Spark 
• Python, SQL, Scala 
• Azure Data Factory, Synapse Analytics 
• ETL, Data Modeling, Performance Tuning 
• Cloud platforms: Azure 
• CI/CD and Git integration workflows 
 
Must have and Good to have skills: Databricks, Apache Spark, Azure Data Factory, Synapse Analytics 
 
Number of years experiences needed: 4-5 years 
 
Shift Schedule: EMEA 
 
Work Set up: Hybrid 
 
Number of days in a month or week that needs to be in the office: 2 x A week (can be discussed) 
 
Project Location (During onsite): Uptown Tower 3, BGC Taguig City

Microsoft Azure Data Services

Required Skill: Expert proficiency in SAP Master Data Migration. 
- Strong understanding of data management principles and practices. 
- Experience with data migration tools and techniques. 
 
Must have and Good to have skills: 
 
Familiarity with SAP modules and their integration with master data. 
- Ability to analyze and resolve data quality issues effectively. 
- Skills and knowledge in Materials Management (MM), including procurement processes, inventory management, and material master data handling. 
 
Number of years experiences needed: 3 years 
 
Shift Schedule: Morning Shift 
Work Set up: Hybrid 
Number of days in a month or week that needs to be in the office: 4 days/month 
Location (During onsite): Uptown 2 Taguig

SAP Master Data Migration

<ul>
	<li>Bachelor’s degree in Information Technology, Computer Science, or a related field.</li>
	<li>3–5 years of professional experience as a Data Engineer or in ETL-focused roles.</li>
	<li>Strong expertise in ETL tools, particularly Informatica, with hands-on experience in data integration and transformation.</li>
	<li>Proficiency in Azure Databricks for data engineering, processing, and advanced analytics.</li>
	<li>Solid understanding of data pipeline design, optimization, and automation.</li>
	<li>Strong knowledge of SQL and relational databases, with experience in query optimization and performance tuning.</li>
	<li>Familiarity with Python or other programming/scripting languages for data manipulation and workflow automation.</li>
	<li>Experience working with cloud-based data platforms (Azure preferred) and integration with enterprise BI/reporting tools.</li>
	<li>Knowledge of data governance, quality, and security best practices.</li>
	<li>Strong problem-solving, analytical, and communication skills, with the ability to collaborate with cross-functional teams.</li>
</ul>

Senior Data Engineer ] Azure Databricks

Key Responsibilities:

<ul>
	<li>Data Transformation: Utilize SQL and Python scripting to clean, transform, and aggregate complex, messy datasets from various sources, preparing them for analysis.</li>
	<li>ETL Support: Collaborate with Data Engineering to monitor, troubleshoot, and optimize data loading and transformation workflows (ETL/ELT)</li>
	<li>Reporting &amp; Visualization: Design, develop, and maintain high-impact dashboards and reports using Power BI to track key business metrics (KPIs).</li>
	<li>Advanced Calculation: Apply DAX (Data Analysis Expressions) to create sophisticated measures, calculated columns, and complex aggregations within Power BI models.</li>
	<li>Business Insight: Conduct deep-dive analyses to identify trends, root causes, and business opportunities, presenting findings clearly to non-technical stakeholders.</li>
	<li>Data Governance: Ensure data accuracy, consistency, and compliance across all reports and analyses.</li>
</ul>

Data Analyst [ ETL | Python | SQL]

The tasks/responsibilities that the role performs to address requirements in Key Result Areas:

<ul>
	<li>Implement and manage tools and applications that enhance productivity and user experience on enterprise data platforms, such as data warehouse tools, data access management tools, metadata management tools (including data catalogs and lineage tracking), and data quality monitoring tools</li>
	<li>Configure and implement security modules of enterprise data platforms to ensure controlled and encrypted network access, encrypted storage, data masking, and data integrity, including data validation, quality checks, integrity constraints, and checksums/hashing for accuracy and trustworthiness.</li>
	<li>Develop and maintain the data lifecycle management, specifically backup, archiving, recovery, and purging data from enterprise data platforms.</li>
	<li>Proactively identify and implement API-driven automation solutions to streamline data security, access controls, metadata management, and data lifecycle management processes on enterprise data platforms</li>
</ul>

The Knowledge, Skills, and Behaviors indicating how tasks/responsibilities will be performed:

<ul>
	<li>Strong understanding of data management and governance practices, including metadata management, data quality management, master data management, and data lifecycle management</li>
	<li>Ability to collaborate with diverse stakeholders and effectively communicate technical concepts to both technical and non-technical audiences.</li>
	<li>Keeps up-to-date with the latest technologies and trends in data security, access control, automation, data lifecycle management, and metadata management</li>
	<li>Proficient in Python programming to automate data security and access control tasks, metadata management, and data lifecycle management processes. This includes developing and maintaining automation scripts, as well as building web applications and tools using frameworks like Django to enhance the enterprise data platform functionality and user experience.</li>
	<li>Ability to analyze complex data challenges and design effective solutions.</li>
	<li>Flexibility to learn new tools, adapt to changing technologies, and solve unexpected challenges.</li>
</ul>

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