Senior Data Analytics Engineer (Manager Level | Individual Contributor)
A senior individual contributor role at Sutherland Global in Taguig focused on migrating legacy BI/reporting to modern cloud data platforms: building enterprise data pipelines and semantic models with SQL, Power BI/DAX, PySpark, Python, and Databricks on Azure/AWS, while partnering with global stakeholders.
- Compensation
- Not disclosed
- Location
- Taguig, Philippines
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 4+ years
- Category
- Data analytics
- Posted
Skills
Must have
- 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 using Git and modern software development practices
- Strong stakeholder management and requirements-gathering skills
- Excellent verbal and written English communication skills
Nice to have
- 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
- Exposure to analytics, machine learning, or data science environments
Full description
Company Description:
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.
Job Description:
*For Pooling Purposes*What You'll DoLead Enterprise Data Modernization Initiatives
- 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.
- Ensure data quality, accuracy, and seamless transition through comprehensive validation and testing.
Design & Build Scalable Data Platforms
- Develop, enhance, and maintain enterprise-grade data pipelines and data products.
- Build efficient data transformation frameworks using modern analytics engineering practices.
- Optimize data models, processing frameworks, and reporting performance.
- Establish scalable solutions that support future analytics, reporting, and machine learning initiatives.
Partner with Business & Analytics Leaders
- Collaborate with data scientists, analysts, and business stakeholders to translate requirements into technical solutions.
- Serve as a trusted advisor on data architecture, reporting strategy, and platform capabilities.
- Support strategic and ad hoc analytics requests through reliable, well-governed data assets.
- Communicate technical concepts effectively to both technical and non-technical audiences.
Drive Operational Excellence
- Implement best practices for data governance, version control, documentation, and deployment.
- Monitor platform performance and proactively identify optimization opportunities.
- Contribute to continuous improvement initiatives across analytics and data engineering functions.