Top Data Analyst Jobs in Manila

Support finance transformation by automating processes, building ETL pipelines, managing MI/BI dashboards and data models (Alteryx, SQL, Power BI), improving data quality, and delivering projects with stakeholder management across Finance, IT, Compliance and Risk.

Design, develop, and maintain interactive Tableau dashboards; gather stakeholder requirements; optimize SQL queries and data models; ensure data accuracy; produce reports and provide dashboard support and troubleshooting.

Analyze and manage SAP master data in an S/4HANA environment. Support MDG/MDM processes, data quality checks, remediation, migration activities, governance, reporting, and documentation while collaborating with data owners and technical teams.

Maintain and improve enterprise data quality and governance for sales systems. Investigate and remediate data issues (deduplication, enrichment, hierarchy maintenance), validate customer and account relationships, monitor quality metrics, partner with cross-functional teams, and support stewardship and governance initiatives to enable accurate reporting and sales productivity.

The Data Analyst will design and maintain dashboards using Tableau and Power BI, analyze data for insights, and support PMO initiatives. Collaboration with leadership and ensuring data quality are key responsibilities.

Own end-to-end mobile and transaction feed analytics for Payments: define tracking, standardize merchant/transaction categorization, build dashboards and reports, monitor payment metrics, support forecasting and financial reporting, partner with product and engineering, and deliver stakeholder presentations and ad-hoc deep-dive analyses.

Lead Data Analyst responsible for gathering requirements, building reusable data models and dashboards, performing analyses and A/B tests, documenting and ensuring data quality, promoting self-service BI, and partnering with data teams and stakeholders to shape the data platform and measure impact.

As a Cricket Data Analyst, you will utilize cricket expertise to provide real-time insights, manage data quality, and support client inquiries while analyzing sports pricing data.

The Data Analyst Intern will assist the Business Development team by creating automated reports, analyzing data, ensuring data integrity, and visualizing insights using dashboard tools.

The Business Systems Analyst will update data in Salesforce, manage projects, collaborate across departments, conduct business analysis, and document processes.

The Senior Financial Data Analyst manages market and master data collection and analysis, ensuring compliance with SLAs and operational risk frameworks to support client needs and improve processes.

Develop, automate, and maintain ETL pipelines and python-based solutions to convert legacy Excel processes, reconcile financial datasets, test and deploy scripts, and improve fund accounting and operational workflows across teams.

Freelance Looker Data Analyst (10-20 hrs/week) building and consolidating Looker dashboards and Explores, partnering with cross-functional teams to investigate trends, produce actionable insights, maintain metric definitions, and document reporting standards for scalable self-serve analytics.

The Finance Data Analyst will support financial analysis, reporting tasks, and decision-making by collaborating with teams to deliver insights and manage financial data efficiently.

The Data Analyst (HRIS) will collaborate with stakeholders to define data needs, prepare reports, perform statistical analyses, and ensure data security while delivering insights and assisting with data projects.

The Data Analyst Consultant will gather, analyze, and interpret data to support business decisions, utilizing various tools and ensuring alignment with business objectives.

Own and analyze marketing channel/program performance end-to-end. Build/maintain GA4 and Salesforce Marketing Cloud dashboards, perform attribution and ROI analysis, translate data into stakeholder-ready recommendations, identify data quality issues, and mentor junior analysts.

Maintain and refresh marketing dashboards, pull and validate campaign performance data, perform QA on data feeds, support ad hoc requests, document report logic, and escalate anomalies to senior analysts.

Lead marketing analytics for US marketing leadership: design scalable measurement frameworks, run advanced attribution and cohort analyses, build dashboards and self-service reporting, own data governance across GA4/Salesforce/Adobe, mentor junior analysts, and present recommendations to senior stakeholders to drive business impact.

Analyze large-scale on-chain data to detect anomalous transactions, develop detection mechanisms and risk monitoring frameworks, apply supervised and unsupervised ML, identify malicious accounts via community-discovery algorithms, and design integrated on-chain/off-chain prevention and control systems.

Support handset installment financing risk operations by extracting, validating, and maintaining risk datasets; produce regular and ad-hoc reports; monitor key risk indicators and anomalies; develop and maintain dashboards and documentation to support risk, fraud, and collections teams.

As a Databricks Data Analyst, you will support data pipeline validation, monitor ingestion jobs, perform schema checks, and manage documentation.

Own data quality and root-cause analysis for prediction issues: detect anomalies, trace sources, fix processes, automate QA/reporting with Python and SQL, maintain dashboards, and partner with Data Science, Engineering, Product, and Commercial teams to improve prediction performance and customer-facing analytics.

Support data integrations and quality by checking ingested/system-generated data for anomalies, building and running QA checks and automations with Python and SQL, assisting on customer data queries and dashboards, and documenting findings to improve prediction reliability.

Lead end-to-end analytics initiatives: build and automate ETL/ELT pipelines, perform data engineering, develop dashboards and predictive models, enforce data governance and quality, validate models, and communicate insights to business and executive stakeholders.