100 Data Pipelines jobs in the Philippines

The Lead of Data Architecture in the banking sector will be responsible for developing and managing data architecture strategies and systems, focusing on the unique needs of financial services, including data security, regulatory compliance, and customer data management.

Key Responsibilities:

1. Banking-Specific Data Architecture Design and Management:

· Develop and maintain data architecture tailored to banking industry needs, including retail banking, transaction banking, investment banking, and risk management.

· Design robust database solutions for handling large volumes of financial transactions and customer data.

· Ensure compliance with financial regulations in all data initiatives.

1. Data Governance and Compliance:

· Implement data governance frameworks specifically designed for banking operations.

· Ensure data accuracy, integrity, and compliance with financial industry standards and regulations.

· Develop and enforce policies for data privacy, security, and ethical use.

· Implement and guide metadata management strategies as aligned with data strategy of the bank.

1. Leadership in Financial Data Management:

· Manage a team of data architects, data modelers, and data mappers specializing in financial systems.

· Drive the adoption of data warehousing, advanced data analytics, and business intelligence in banking operations.

· Promote a culture of data-driven decision-making within the organization.

1. Technology Integration and Innovation:

· Evaluate and implement banking-specific data management tools and software.

· Integrate emerging technologies like AI, machine learning, and blockchain into the data architecture.

· Oversee the transition to cloud-based data management solutions, ensuring security and regulatory compliance.

1. Project Management and Collaboration:

· Coordinate with IT, risk management, and financial departments to align data architecture with business goals.

· Oversee banking-specific data architecture projects, ensuring they meet industry standards and business objectives.

· Liaise with external stakeholders, including regulatory bodies and technology partners.

Qualifications:

· Advanced degree in Computer Science, Information Technology, Finance, or a related field.

· Extensive experience in data architecture within the banking or financial services industry.

· In-depth understanding of financial regulations affecting data management.

· Proven leadership experience in a banking technology environment.

Skills:

· Expertise in financial databases, data modeling, and ETL processes specific to banking.

· Proficiency in data security and compliance technologies.

· Knowledge of fintech innovations and their applications in data architecture.

· Strong strategic planning, communication, and stakeholder management skills.

· Familiarity with cloud services (AWS, Azure) tailored for financial services.

· Professional certifications relevant to data management and financial services.

Experience Levels

Data Architect

· 5 to 8 years of experience focusing on data warehousing in a financial setting.

· Strong understanding of risk management, financial reporting, and transaction processing systems.

Senior Data Architect

· More than 8 years of experience with extensive knowledge in managing comprehensive data architectures in the banking and finance industry.

· Demonstrated leadership in driving major data initiatives and mentoring team members.

Job brief

We are seeking a visionary
Head of
Data Architecture
for a global company building AI platforms from scratch to lead the design and execution of our enterprise-wide data backbone. This leader will unify data across CAD, Finance, Operations, and GTM functions, ensuring our organization has a trusted, scalable foundation for analytics, AI, and business decision-making.

Responsibilities

• Design, implement, and own the enterprise-wide data architecture that connects critical business domains (CAD, Finance, Operations, GTM).
• Lead the development and maintenance of data models, pipelines, lineage, quality frameworks, adnd governance standards.
• Ensure the delivery of reliable, well-documented datasets to enable AI, ML, and advanced analytics use cases.
• Establish and enforce best practices for data management, scalability, and cloud-native architectures.
• Collaborate with cross-functional stakeholders to translate business needs into data solutions.
• Build, lead, and mentor a high-performing team of data engineers and architects.

Requirements

• Proven track record of designing and scaling enterprise-level, cloud-native data platforms beyond reporting and BI.
• Hands-on expertise with Snowflake or BigQuery, along with modern orchestration and transformation tools (e.g., dbt, Airflow) in AWS, GCP, or Azure environments.
• Demonstrated impact through enabling AI/ML and advanced analytics initiatives
• Strong leadership presence: ability to recruit, develop, and inspire data engineering talent.
• Excellent communication and collaboration skills, with experience working across executive, technical, and operational teams.

We are seeking a visionary Head of  Data Architecture  for a global company building AI platforms from scratch to lead the design and execution of our enterprise-wide data backbone. This leader will unify data across CAD, Finance, Operations, and GTM functions, ensuring our organization has a trusted, scalable foundation for analytics, AI, and business decision-making. 

• Design, implement, and own the enterprise-wide data architecture that connects critical business domains (CAD, Finance, Operations, GTM).
•  Lead the development and maintenance of data models, pipelines, lineage, quality frameworks, adnd governance standards.
• Ensure the delivery of reliable, well-documented datasets to enable AI, ML, and advanced analytics use cases.
• Establish and enforce best practices for data management, scalability, and cloud-native architectures.
• Collaborate with cross-functional stakeholders to translate business needs into data solutions.
• Build, lead, and mentor a high-performing team of data engineers and architects.

• Proven track record of designing and scaling enterprise-level, cloud-native data platforms beyond reporting and BI.
• Hands-on expertise with Snowflake or BigQuery , along with modern orchestration and transformation tools (e.g., dbt, Airflow ) in AWS, GCP, or Azure environments.
• Demonstrated impact through enabling AI/ML and advanced analytics initiatives
• Strong leadership presence: ability to recruit, develop, and inspire data engineering talent.
• Excellent communication and collaboration skills, with experience working across executive, technical, and operational teams.

We are seeking an experienced and strategic Director of Data Architecture to lead the design and implementation of an enterprise-wide data backbone that seamlessly integrates data across CAD, finance, operations, and go-to-market functions. This role will be responsible for building and maintaining robust, scalable data infrastructure that supports our business intelligence, analytics, and AI capabilities.

KEY RESPONSIBILITIES

• Design and implement enterprise‑wide data backbone that unifies CAD, finance, ops, and GTM data.
• Own data models, pipelines, quality, lineage, and governance.
• Enable AI/analytics by delivering reliable, well‑documented datasets.

QUALIFICATIONS

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.
• 10+ years of experience in data architecture, data engineering, or related fields, with at least 5 years in leadership roles.
• Proven track record of designing and implementing enterprise-scale, cloud-native data platforms beyond traditional reporting.

• Hands-on expertise with:

• Cloud platforms: AWS, GCP, or Azure.

• Data warehousing: Snowflake, BigQuery, or similar.

• Data pipeline/orchestration: dbt, Airflow, or equivalent.

• Experience enabling AI/ML or advanced analytics use cases through robust data foundations.

• Strong background in data governance, quality, and security frameworks.
• Demonstrated ability to recruit, mentor, and lead data engineering teams.
• Excellent communication and collaboration skills, with ability to influence technical and business stakeholders.

About the Position: Lead Consultant Data Architecture & Engineering (GDC) | Remote

Work Arrangement: Fully Remote

Schedule: Midshift

At least 5 years of relevant experience and at least 4 years of relevant leadership experience is needed.

Job Overview:

**Leadership Development** This role offers opportunities to enhance your technical leadership skills, including making technical decisions, mentoring junior team members, and building relationships with project, client, and company leadershipall while remaining actively involved in your technical domain.

**Technology Focus & Growth** Our primary focus is on Azure, providing numerous chances to develop your expertise within the Microsoft and Azure ecosystems in an environment dedicated to technical excellence and exceptional client experiences. Just six months with our team can equate to years of experience elsewhere.

**Partnerships & Opportunities** Our strong global partnership with Microsoft ensures access to innovative Azure projects and direct collaboration with the platforms creatorsan advantage not commonly found elsewhere.

**Compensation & Culture** We offer a competitive salary, allowances, standard benefits, and performance-based bonuses (quarterly and annually). Our company fosters a positive working environment and culture, with flexible options for remote work.

**Core Technical Skills Required:**

• Proven experience leading small to medium technical teams, including task delegation, technical escalation, support, and representing the team in Agile ceremonies and client meetings

• Expertise in designing and implementing logical and physical data models for cloud and hybrid data warehouse environments

• Experience in developing data architectures supporting diverse data formats: structured, semi-structured, and unstructured data

• Hands-on involvement in full lifecycle data warehouse projects

• Knowledge of data architecture necessary for data integration processes

• Proficiency with data modeling tools such as ER/Studio, ER/Win, or similar

• Familiarity with Microsoft Azure Data Platform services like Azure Data Lake Storage, Azure Blob Storage, Azure Synapse, Azure Data Factory, Azure SQL Database, Logic Apps, and APIs

• Demonstrated ability to quickly learn, adapt, and apply new technologies

• Experience in data profiling and mapping source-to-target data transformations

• Ability to provision and configure Azure data services

**Detailed Technical Skills:**

• Python and SQL scripting

• SQL and PySpark

• General cloud architecture skillscapable of translating requirements into data pipeline solutions

• API development knowledge; candidates with API creation skills are preferred

**Preferred Skills, Experience, & Certifications:**

• Microsoft Fabric

• Microsoft Azure Cosmos DB, Data Flows, ExpressRoute, Azure Active Directory

• Experience designing migration strategies from on-premise environments to Azure

• Power BI and semantic data modeling

• AWS Glue and Azure Data Factory

• AWS S3 and Azure Blob Storage

• AWS Athena and Azure Databricks

• AWS Redshift and Azure Synapse Analytics

• AWS ECS and Azure AKS

Supports pre- and post-deployment activities related to data pipelines and product integrations, including manual data ingestion. This role focuses on assisting with the maintenance and troubleshooting of diverse data stack tools.

Key Responsibilities

• Assist in client-facing technical support relating to data ingestion and data configurations.
• Assist in monitoring and maintaining data pipelines, including those built with tools like Matillion and other orchestration frameworks.
• Manage and troubleshoot pre-written scripts, including PHP or similar languages, that load data into a Postgres database.
• Troubleshoot and resolve data integration issues across internal systems, ensuring data accuracy and pipeline stability.
• Document standard procedures, pipeline behaviors, and recurring technical issues.
• Collaborate with fellow data engineers, Support, and product teams to ensure smooth deployment and post-deployment operations.
• Escalate complex technical challenges to senior team members as needed.

Qualifications

• Bachelor's Degree holder.
• Familiarity with SQL or similar data transformation tools.
• Familiarity with PHP or similar, python.
• Experience with data orchestration tools like Matillion, with awareness of other frameworks such as Airflow or Prefect.
• Strong problem-solving and collaboration skills.
• Eagerness to learn and grow in a fast-moving, research-informed environment.
• Experience in a client-facing role assisting enterprise users.