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Reads like a Data Engineer role: pipelines and data infrastructure.
Taguig, NCR, Philippines
Live, first seen by us 28 days agoWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Migrate legacy reporting and analytics environments to modern cloud platforms
Analyze BI models, SQL workloads and reporting logic to find optimizations
Build and maintain enterprise data pipelines and transformation frameworks
Validate data quality and accuracy during each migration step
Translate business requirements into technical data solutions
Drive the migration of legacy reporting and analytics environments to modern cloud-based platforms.
Analyze existing BI models, SQL workloads, and reporting logic to identify optimization opportunities.
Develop, enhance, and maintain enterprise-grade data pipelines and data products.
Ensure data quality, accuracy, and seamless transition through comprehensive validation and testing.
Collaborate with data scientists, analysts, and business stakeholders to translate requirements into technical solutions.
Bachelor's degree in Computer Science, Information Technology, Data Analytics, Engineering, or a related field.
4+ years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or Data Platform Development.
Strong expertise in SQL, including advanced query development, optimization, and stored procedure logic.
Experience working with Power BI, semantic models, and DAX-based reporting environments.
Hands-on experience with Spark, PySpark, Spark SQL, or similar big data technologies.
Proficiency in Python for data processing, automation, and analytics.
Experience with Databricks, Delta Lake, Databricks SQL, DLT Pipelines, and Unity Catalog.
Experience leading or contributing to cloud migration and data modernization initiatives.
Knowledge of modern data warehousing, lakehouse architecture, and analytics platforms.
Experience supporting high-volume, customer-facing, or enterprise-scale operations.
Required Qualifications - Bachelor's degree in Computer Science, Information Technology, Data Analytics, Engineering, or a related field. - 4+ years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or Data Platform Development.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 28
Similar jobs usually come down between day 6 and day 54.
From 10,782 similar postings that came down. Coming down is not always a hire.
6 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Hands-on experience with Spark, PySpark, Spark SQL, or similar big data technologies. - Proficiency in Python for data processing, automation, and analytics. - Experience using Git and modern software development practices.
- Drive the migration of legacy reporting and analytics environments to modern cloud-based platforms. - Analyze existing BI models, SQL workloads, and reporting logic to identify optimization opportunities. - Convert complex business and reporting logic into scalable cloud-native data solutions.
- 4+ years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or Data Platform Development. - Strong expertise in SQL, including advanced query development, optimization, and stored procedure logic. - Experience working with Power BI, semantic models, and DAX-based reporting environments.
- Experience working with Power BI, semantic models, and DAX-based reporting environments. - Hands-on experience with Spark, PySpark, Spark SQL, or similar big data technologies. - Proficiency in Python for data processing, automation, and analytics.
Preferred Qualifications - Experience with Databricks, Delta Lake, Databricks SQL, DLT Pipelines, and Unity Catalog. - Experience leading or contributing to cloud migration and data modernization initiatives.
- Knowledge of modern data warehousing, lakehouse architecture, and analytics platforms. - Databricks, Azure, AWS, or related cloud certifications. - Experience supporting high-volume, customer-facing, or enterprise-scale operations.
- Strong expertise in SQL, including advanced query development, optimization, and stored procedure logic. - Experience working with Power BI, semantic models, and DAX-based reporting environments. - Hands-on experience with Spark, PySpark, Spark SQL, or similar big data technologies.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
*For Pooling Purposes*
What You'll Do
Lead Enterprise Data Modernization Initiatives
Design & Build Scalable Data Platforms
Partner with Business & Analytics Leaders
Drive Operational Excellence
What We're Looking For
Required Qualifications
Preferred Qualifications
Why Join Us?
Own High-Impact Data Initiatives
Take the lead on strategic data transformation projects that directly influence business performance and decision-making.
Work Directly with Global Leadership
Partner with senior leaders and cross-functional teams in a highly collaborative, fast-paced environment where your expertise is valued.
Shape a Modern Analytics Ecosystem
Play a foundational role in building scalable cloud-based data platforms that enable advanced analytics, AI, and future innovation.
Accelerate Your Career
Gain exposure to modern technologies, enterprise-scale datasets, and complex business challenges while expanding your leadership influence as a senior individual contributor.
Transform Enterprise Data. Build the Future of Analytics.
Are you passionate about designing modern data platforms and solving complex analytics challenges at scale? We're looking for a Senior Data Analytics Engineer to lead the evolution of our next-generation data ecosystem.
This is a highly visible individual contributor role for a seasoned data professional who thrives at the intersection of data engineering, analytics, business intelligence, and cloud modernization. You will play a critical role in transforming legacy reporting environments into scalable, high-performance cloud-based solutions while partnering with global stakeholders to deliver insights that drive business decisions.
If you enjoy owning end-to-end data solutions, optimizing enterprise reporting, and building robust data pipelines that empower analytics and AI-driven initiatives, this opportunity is for you.
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Taguig, NCR, Philippines
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