Sr Manager-Data Platforms sn

APAC IT has built an Enterprise Information Management (EIM) system, One Source of Truth (OSOT), which leverages US ATLAS and comprises data lakes, a data warehouse, data marts, and data processing pipelines on cloud infrastructure. OSOT is live in Production, supporting financial analysts, product performance, and operations across all APAC businesses. The next phase of this strategy is a full migration of OSOT onto the Databricks Data Intelligence Platform, consolidating data engineering, analytics, and AI/ML on a single lakehouse foundation.

The Senior Manager - Data Platforms is responsible for end-to-end ownership of Data Engineering in APAC. A primary mandate of this role is to lead the migration of the current OSOT solution onto Databricks - re-platforming data lakes, warehouse, marts, and pipelines onto a Unity Catalog-governed lakehouse using Delta Lake, Databricks SQL, and Lakeflow / Delta Live Tables. The role works continually with OSOT business stakeholders (APAC) and Global teams (EDP Platform team) to execute new data strategies across the APAC product suite, including Device Protection, Upgrade, Open Market, Trade-In, and Direct to Consumer.

Equally central to the role is enabling Generative AI on top of the Databricks lakehouse. The incoming person will design how Databricks integrates with AI platforms such as Anthropic Claude and OpenAI - governing data access, grounding models on APAC enterprise data (RAG), and operationalizing AI use cases through Databricks Mosaic AI, Model Serving, AI Gateway, and Vector Search. They will design, execute, and introduce modern data and AI tooling to support APAC's business needs across data ingestion, processing, report definition, and requirements gathering with business teams.

The role requires stakeholder management across many functions (account teams, Finance, CARE, and SCM) and close partnership with Global IT teams (US EDP, DAX, Security) to ensure data security, governance, and compliance - particularly around responsible and secure use of LLMs - as well as managing the delivery of current in-flight data projects. Additionally, the person will introduce AI and ML technologies to support advanced analytics in Risk, Supply Chain, and other Direct to Consumer product offerings.

Key Accountabilities

OSOT to Databricks Migration & Platform Ownership

. Lead the end-to-end migration of the current OSOT solution (data lakes, data warehouse, data marts, and Talend/SQL/Python pipelines) onto the Databricks Data Intelligence Platform, defining the target lakehouse architecture, migration roadmap, sequencing, and cutover strategy with minimal disruption to production.

. Re-architect OSOT into an APAC-specific Enterprise Data Platform on Databricks using Delta Lake, the medallion (bronze/silver/gold) architecture, Unity Catalog for governance and lineage, and Lakeflow / Delta Live Tables and Workflows for orchestration.

. Migrate and modernize ETL/ELT from existing tooling (Talend, SQL, Python) to Databricks-native pipelines (PySpark, Spark SQL, Databricks SQL), establishing reusable frameworks for ingestion, transformation, data quality, and metadata/dependency management.

. Build data pipelines, architectures, and curated data sets from raw, loosely structured data, and stand up Databricks SQL warehouses to serve BI and self-service analytics for APAC businesses.

. Own a modern data engineering operating model that follows DevOps/DataOps principles - CI/CD for notebooks and jobs (Databricks Asset Bundles, Git integration), automated testing, and infrastructure-as-code.

AI Platform Integration (Claude, OpenAI) on Databricks

. Define and own how Databricks works with external AI platforms such as Anthropic Claude and OpenAI - establishing secure, governed integration patterns via Databricks Mosaic AI, Model Serving, and AI Gateway (external model endpoints) so LLMs can be consumed centrally with rate limiting, logging, and cost controls.

. Use Unity Catalog and Databricks governance to control which enterprise data is exposed to AI models, ensuring PII protection, access policies, and auditability before any data reaches Claude or OpenAI.

. Enable Retrieval-Augmented Generation (RAG) on APAC enterprise data using Databricks Vector Search and feature/embedding pipelines, grounding Claude and OpenAI responses in trusted OSOT data for use cases such as analyst copilots, document intelligence, and natural-language querying of the lakehouse.

. Operationalize GenAI use cases end-to-end - prompt management, evaluation, monitoring, and MLOps - using Databricks Mosaic AI (MLflow, Model Serving, AI Gateway, and agent/evaluation frameworks).

. Partner with Global IT and Security to define responsible-AI guardrails for LLM usage (data residency, prompt/response logging, content safety, and acceptable-use policies for Claude and OpenAI).

Data Modeling, Analytics & Stakeholder Delivery

. Interface with cross-functional teams (Finance, Risk, SCM, and Product) to design and build data models on the lakehouse that provide actionable insights into key business performance metrics and support the commercial team.

. Leverage cloud-based lakehouse architecture and Databricks ML capabilities to deliver optimized ML and AI models at scale.

. Work closely with leaders across data architecture, enterprise architecture, data science/analytics, and domain experts to build and maintain roadmaps aligned to the IT strategy.

. Act as a strategic thinker with a holistic vision, with specific focus on identifying and automating existing manual processes - including AI-assisted automation - to drive key business performance.

. Participate in project working groups and assist in tracking project milestones and deliverables.

Critical Competencies / Critical Success Factors

. Bachelor's degree required master's degree (or equivalent) in computer science, engineering (all branches), mathematics, or a related field preferred.

. 8+ years of experience with public and private cloud solutions, including building and maintaining a data ecosystem that includes an ERP environment.

. 8+ years of experience designing and building data-intensive solutions using distributed computing.

. Hands-on experience with the Databricks Data Intelligence Platform - Delta Lake, Unity Catalog, Databricks SQL, Lakeflow / Delta Live Tables, Workflows, and the medallion architecture experience leading a migration onto Databricks is strongly preferred.

. Experience integrating and operationalizing LLM/GenAI platforms (e.g., Anthropic Claude, OpenAI) - including Databricks Mosaic AI, Model Serving, AI Gateway, Vector Search, and RAG patterns - with appropriate governance and security.

. 6+ years of programming experience with SQL, Python, Scala, and Java.

. Experience with distributed data streaming frameworks such as Spark Structured Streaming, Apache Flink, and Kafka.

. OLAP experience (Cubes, MSSQL) and data warehouse usage/optimization experience (Databricks SQL, Redshift, Hive, Snowflake).

. Experience building data visualizations or analytics (e.g., Power BI, Databricks dashboards, SSRS).

. Experience building machine learning models familiarity with MLflow and modern MLOps practices.

. Strong analytic skills and understanding of statistical methodologies.

. Strong knowledge of data governance, security, and compliance, including responsible/secure use of AI and LLMs.

. Ability to communicate effectively with external clients and internal teams and manage expectations.

. Demonstrated ability to work as an effective team member - sharing knowledge and helping others meet team priorities - while also working independently as an effective decision-maker.

. Good verbal, written, and presentation skills able to engage with offshore-based development and support teams.

. An effective troubleshooter, able to analyze problems and develop/recommend solutions, with a willingness to learn and adapt to strategic initiatives in the pipeline.

What you need to do now

If you're interested in this role, click apply now to forward an up-to-date copy of your CV, or call Shabnam at Hays on +65 60271964 or email [Confidential Information] for a confidential discussion.

Referrals are welcome.

Registration ID No. R1873584 | EA License number: 07C3924 | Company Registration No. 200609504D