Senior Manager – Data Platforms

Synechron; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Synechron in Singapore seeks a Senior Manager - Data Platforms to lead the Databricks migration and APAC data platform ownership. You will architect modern data pipelines and govern data assets while enabling analytics across the APAC region.

You will drive AI platform integration (Claude/OpenAI) and implement DevOps/DataOps practices, ensuring robust data governance and secure AI usage for business insights.

Qualifications

• Bachelor's degree in CS/engineering or math.
• 8+ years with public and private cloud solutions and data ecosystem.
• 6+ years programming with SQL, Python, Scala, and Java.
• Experience with distributed data processing (Spark, Flink, Kafka).
• Experience integrating and operationalizing LLM/GenAI platforms.
• Strong knowledge of governance, security and compliance.

Responsibilities

• Lead OSOT to Databricks migration and platform ownership.
• Architect APAC Data Platform on Databricks with Delta Lake.
• Migrate ETL/ELT to Databricks-native pipelines.
• Build data pipelines and Databricks SQL warehouses for BI.
• Own data engineering operating model with DevOps/DataOps.
• Define AI platform integration patterns with Claude/OpenAI.
• Ensure governance and security for data and AI usage.

Skills

Databricks

Python

SQL

Scala

Java

Spark

Kafka

Data governance

MLflow

MLOps

LLM governance

Education

Bachelor's degree in CS/Engineering/Math

Master’s degree in CS/Engineering/Math

Tools

Delta Lake

Unity Catalog

Databricks SQL

Lakeflow

Delta Live Tables

MLflow

Model Serving

Job description

We have immediate opportunity for Senior Manager - Data Platforms

Job Role: Senior Manager - Data Platforms

Experience- 12 Years - 15 Years

Notice Period: Immediate to 30 days.

About Company:

At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honoured with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 14,700+ and has 55 offices in 20 countries within key global markets. For more information on the company, please visit our website or LinkedIn community.

Diversity, Equity, and Inclusion

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and an affirmative-action employer. Our Diversity, Equity, and Inclusion (DEI) initiative 'Same Difference' is committed to fostering an inclusive culture - promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant's gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

Job Description:

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.