Dept Head Analytics Data Mgt & Platform

Permata Bank; Tangerang Selatan; On-site; IDR 1,800,000,000 - 3,000,000,000; Full time

Job summary

Permata Bank is seeking a veteran Data Engineering leader to drive cloud data architecture, DWH/Lakehouse strategy, and Databricks adoption across the enterprise. You will partner with AI/ML teams, implement robust governance, and own the BI metrics roadmap while mentoring multinational engineering teams.

Ideal candidates bring 10+ years in data engineering, strong leadership, and hands-on experience with cloud data platforms in regulated banking environments.

Qualifications

• 10+ years in Data Engineering and Enterprise Analytics.

Responsibilities

• Lead end-to-end cloud data architecture and DWH/Data Lakehouse migration.
• Oversee Databricks integration and cost optimization.
• Shape AI enablement with MLOps and feature stores.
• Enforce data governance, security, and quality standards.
• Own BI roadmap and SVOT alignment across tools.
• Lead and mentor cross-border data engineering teams.

Skills

Cloud data platforms

Databricks platform

AI/ML data infra

Streaming real-time data

Data security & governance

ETL/ELT frameworks

BI visualization

Cost governance

Cross-functional leadership

Stakeholder management

Education

Bachelor’s or Master’s degree in Computer Science / IT / Software/Data Engineering

Tools

Databricks

Apache Spark

MLflow

Airflow

dbt

Kafka

Debezium

Tableau

PowerBI

Looker

Job description

Company Description :

We are one of the top 10 biggest banks in terms of assets in Indonesia and listed in the Indonesia Stock Exchange, that offer banking products and services that help people and companies to succeed, creating wealth and growth through our Retail Banking, SME and Wholesale businesses.

Why Permata Bank ?

Here at Permata Bank, you will Learn, Grow, and Make A Difference

You will have the appetite and the ability to learn many things, challenged to grow beyond ways you can imagine, and see the incredible difference you would have made along the journey.

This is our platform for you. We cannot promise a smooth ride, but rest assured, it is going to be a meaningful journey!

Learn : We always think innovatively to improve the way we work, making it easier, better and faster.

Grow : We provide excellent service to customers and encourage excellent performance in our daily work.

Make a difference : We understand each other and together build strong relationships with internal and external parties based on mutual respect.

Responsibilities:

1. Cloud Data Architecture, Databricks & Engineering Strategy

• Lead the end-to-end cloud strategy, architectural design, and migration/setup of Enterprise Data Warehouses (DWH) and Data Lakehouses across modern cloud environments (AWS, GCP, or Azure).
• Oversee the implementation and optimization of Databricks (Delta Lake, Lakehouse architecture) to unify data engineering, stream processing, and analytics workflows.
• Oversee the design and implementation of highly scalable, configuration-driven ETL/ELT framework architectures across batch, real-time (CDC/Debezium), and unified data layers.
• Drive infrastructure cost optimization strategies across cloud services, DWH, and Databricks compute engines to minimize operational expenditure without compromising performance.

2. AI Enablement & Advanced Analytics Infrastructure

• Partner with Data Science and AI/ML teams to architect data platforms that support Machine Learning operations (MLOps), feature stores, real-time inference pipelines, and enterprise AI integrations.
• Ensure data platforms are optimized for AI readiness, providing clean, high-quality, and scalable datasets for predictive models and generative AI applications.

3. Data Governance, Security & Quality

• Enforce robust cloud and data security measures, including PII data protection, column-level access control, role-based access control (RBAC), data encryption, and audit trails.
• Establish SOPs and guidelines for data creation and pipeline management following industry best practices and regulatory/compliance standards in banking/financial services.
• Oversee enterprise-wide Data Quality Frameworks ensuring Timeliness, Completeness, Consistency, and Uniqueness across both batch and real-time data pipelines.

4. Business Intelligence & Metrics Ownership

• Oversee the BI roadmap to ensure a Single Version of the Truth (SVOT) for key business metrics across modern reporting engines (e.g., Tableau, Metabase, Looker Studio, PowerBI).
• Partner with business units to deliver self-service analytics frameworks that enable fast, reliable, data-driven decision-making.

5. Leadership & Stakeholder Management

• Lead, mentor, and build high-performing, cross-border engineering (Data Engineers, Cloud/Platform Engineers) and Business Intelligence teams.
• Collaborate closely with senior stakeholders across Product Engineering, DevOps, Risk, Finance, Data Science/AI, Operations, Marketing, and Collections to align data platform capabilities with core business goals.

Job Requirements:

Education & Experience:

Education: Bachelor’s or Master’s degree in Computer Science, Information Technology, Software Engineering, Data Engineering, or a related technical field.

Experience:

• 10+ years of hands-on experience in Data Engineering, Data Architecture, and Enterprise Analytics Platform management.
• 4+ years in a senior leadership/management role leading cross-functional or multi-national data engineering and platform teams.
• Hands-on experience setting up and scaling enterprise data platforms in major Cloud environments (GCP, AWS, or Azure).
• Proven expertise in architecting and managing Databricks platform solutions.
• Proven experience in banking, fintech, or financial services environments with strict regulatory and compliance requirements.

Technical & Professional Skills

• Cloud & Databricks Platform Setup: Deep expertise in deploying end-to-end cloud data ecosystems (AWS/GCP/Azure) and managing Databricks Lakehouse platforms (Delta Lake, Apache Spark, MLflow).
• AI & Machine Learning Data Infrastructure: Solid experience building data pipelines that support AI/ML model deployment, feature stores, and real-time analytical feeds for Data Science teams.
• Streaming & Real-Time Data: Strong proficiency with real-time CDC engines (e.g., Debezium, Kafka), schema registries (Protobuf, Avro), and real-time stream processing.
• Data Security & Protection: Hands-on knowledge of PII protection methodologies, cloud governance, column-level tags (e.g., Google Policy Tags / Unity Catalog), role-based access controls, and retention policies.
• ETL/ELT Frameworks: Strong proficiency in configuration-driven ETL frameworks, Airflow, dbt, or modern orchestration engines.
• BI & Visualization: Familiarity with BI stack management (Tableau, Looker, Metabase, PowerBI) to maintain metric standardization (SVOT).
• Cost Governance: Proven track record in DWH and cloud/Databricks compute cost optimization strategies.

Soft Skills & Leadership Capabilities

• Cross-Functional Influence: Strong ability to engage and align with technical (DevOps, Data Science, Core Engineering) and non-technical stakeholders (Risk, Finance, Business Lines).
• Team Empowerment: Passionate about mentoring junior to senior engineers and building a high-performing engineering culture.
• Strategic & Results-Oriented: Strong execution capability under tight deadlines, balancing long-term architectural stability with immediate business needs.

Directorates :

Technology

PT Bank Permata Tbk hereby informs that the company does not impose any charges in the employee recruitment process.