DATA Production Engineer

DATA Production Engineer (Production Support)

Our Client, the wealth management arm of a large Group, is an international company specializing in Information Systems outsourcing and Banking Operations Processing for private banking players.

They provide their customers with an Integrated Information System (S2i), and a full range of digital banking products and services.

They also handle their customers back-office operations from 3 hubs, in Switzerland, Portugal and Singapore.

Their Banking Operations department stands out for the excellence of its unique tailor-made service, recognized by customers and the market alike.

They are looking for a Data Production Engineer based in Singapore to ensure the operational stability and reliability of critical Data production systems in an international environment.

The role is 100% RUN-oriented, focusing on production support, incident management, and data flow reliability, while interacting with a broader Data Platform ecosystem (Kafka, Qlik, databases) maintained by dedicated platform teams.

This position plays a key role in guaranteeing data availability, consistency, and quality across global data flows.

Main missions

Key Responsibilities:

Data Production & RUN Operations (core mission)

. Provide Level 2 / Level 3 production support for Data applications and pipelines.

. Investigate and resolve complex incidents related to:

- data pipelines,

- batch processing,

- global platform performances

. Perform root cause analysis (RCA) and drive corrective and preventive actions.

. Participate in incident calls and ensure proper follow-up until full resolution.

. Contribute to the reduction of recurring production issues.

Monitoring & Stability

. Supervise end-to-end Data processing chains (batch and streaming).

. Improve monitoring, alerting, and proactive detection capabilities.

. Ensure production documentation is up to date (runbooks, operational procedures).

. Support production readiness during releases and changes.

Interaction with the Data Platform ecosystem

. Work closely with dedicated platform teams (DBA, MDW, Build Data).

. Understand Kafka-based data flows and global Data architectures in order to:

- efficiently troubleshoot production issues,

- coordinate with platform and build teams.

Kafka development and maintenance are out of scope but understanding its role in data flows is required.

Technical Environment

Current production environment:

. ODS / traditional Data architectures

. ETL tools (IBM DataStage, Qlik)

. Reporting / data exposure tools (SAP BusinessObjects)

. Databases (IBM DB2, MSSQL, Oracle)

. Linux and Windows environments

Data ecosystem knowledge (expected)

. Kafka (data flow understanding, topics, producers/consumers concepts)

. Qlik (QlikReplicate)

. Cloudera (Spark, Yarn, Python, ...)

. Modern Data Platforms (batch + streaming architectures)

Tool-specific expertise is less important than the ability to operate, stabilize, and troubleshoot complex Data production systems.

Organisation & Constraints

. Standard office hours.

. On-call duty shared with team members.

. Individual contributor role, fully RUN-oriented.

. International context with multiple time zones.