Industry Platforms - Databricks Senior Consultant | Hybrid - Makati

Position Overview

Industry Platforms & Systems Integration (IP&SI) is our client's trusted delivery practice – bringing together platform expertise, systems integration, modern data foundations, and security-by-design to help clients deliver change faster, with confidence. We connect trusted data, modernise core platforms, and uplift capability to reduce cost and risk while enabling resilient, artificial intelligence (AI)-ready operations.

 The MDP Databricks Architect / Consultant / Developer designs, builds and operates modern analytics and data platforms using the Databricks Lakehouse Platform. The role enables organisations to deliver scalable, high-performance, governed data solutions across analytics, business intelligence (BI), data engineering, data science, and artificial intelligence/machine learning (AI/ML) workloads.

 Depending on experience and seniority, the role may be hands-on in solution delivery (Developer / Consultant) or lead platform architecture, standards and data strategy (Architect). The role works closely with business stakeholders, data teams, cloud architects and security teams to ensure the platform is secure, cost-effective and enterprise-ready.

Key Responsibilities

• Design and implement modern data platforms using the Databricks Lakehouse Platform.
• Build ingestion and transformation pipelines using Databricks Workflows, Apache Spark (PySpark / Spark SQL) and Delta Lake, supporting batch, streaming and near real-time processing.
• Architect focus: Define and apply platform standards for data ingestion, modelling, data quality and governance; ensure alignment to cloud, security, identity and cost management requirements.

·       Develop and optimise Databricks (Apache Spark) pipelines and Delta Lake models to enable governed data consumption (for example, Power BI/Tableau) and support analytics, data science, and machine learning (ML) use cases.

• Implement monitoring, performance tuning and cluster optimisation; support CI/CD for notebooks, jobs and data pipelines and contribute to operational runbooks.
• Collaborate with analysts, data scientists and application teams; advise stakeholders on Databricks capabilities and design trade-offs, and mentor junior team members (where applicable).

Skills, Experience and Competencies

Technical Skills

• Strong expertise in Databricks Lakehouse Platform.
• Deep experience with Apache Spark, PySpark, and Spark SQL.
• Knowledge of Delta Lake, data modelling, and performance tuning.
• Experience with streaming data (Structured Streaming, Kafka).
• Understanding of data security, governance, and cost optimisation.

Experience (Role Level Determination)

MDP Databricks Architect

• 10–15+ years of data and analytics experience.
• 7–10+ years designing enterprise scale data platforms.
• Proven experience defining lakehouse architectures and data strategies.

MDP Databricks Senior Consultant

• 6–9 years of data and analytics experience.
• 4–6 years delivering modern data platforms using Databricks.
• Strong delivery, design, and stakeholder engagement skills.

MDP Databricks Developer

• 4–6 years of overall data / analytics experience.
• 2–4 years of hands‑on Databricks and Spark experience.
• Strong focus on development and implementation.

Competencies

• Early alignment and shaping clarifying use cases, data domains, success measures and non-functional requirements, then translating them into a practical Databricks delivery plan.
• Governance and controlled change applying standards and change control (with impact assessment) across notebooks, jobs, pipelines, data models and environments.
• Trusted data, quality by design building Delta Lake pipelines and models with validation, testing, lineage and reconciliation to support analytics and artificial intelligence/machine learning (AI/ML).
• Standardise use patterns, templates and accelerators (including CI/CD and infrastructure as code where relevant) to improve speed and consistency.
• Transparent delivery and operational discipline communicating progress and risks clearly, implement monitoring and observability, and optimising cost and performance for stable operations.

Qualifications and Certifications

• Databricks Certified Data Engineer (Associate / Professional)
• Databricks Certified Data Architect (role dependent). 
• Cloud platform certifications (Microsoft Azure / Amazon Web Services desirable).

What Success Looks Like

• Databricks is established as a scalable and high-performance modern data platform.
• Data pipelines are reliable, efficient and easy to maintain, and analytics and AI/ML workloads run on governed datasets.
• Data is secure, trusted, and widely adopted across the organisation.
• Platform costs and performance are optimised, and Databricks is positioned as a strategic lakehouse foundation.