Lead Data & Integration Engineer

Lead Data & Integration Engineer

Important Information

Location: Singapore

Key Responsibilities

1. System Analysis & Design

Analyse business/technical requirements and translate them into data flows and integration designs

Work with upstream and downstream teams to define data contracts and interfaces

Identify gaps, inefficiencies and risks in current data movement processes

Propose pragmatic solutions balancing speed, quality and maintainability

Integration & Data Movement

Design and implement data movement across systems using:

APIs

SFTP and file based transfers

Batch pipelines

Coordinate integrations across systems in the DataLake ecosystem (Informatica, Cloudera, etc.)

Ensure data is correctly transformed, mapped and delivered to target systems

Troubleshoot integration issues across environments

Data Preparation for GenAI

Support data ingestion and preparation for GenAI use cases:

document ingestion

data aggregation

enrichment and transformation

Work with structured and unstructured data

Ensure data is usable for downstream AI workflows (RAG, search, investigation flows)

You are not asking them to build models, just make data usable for them.

Delivery & Coordination

Work across multiple teams:

data platforms

application teams

infrastructure

security

Support SIT, UAT and production rollouts

Ensure integration reliability, error handling and monitoring

Document flows, mappings and interfaces clearly

Key Requirements

Below are the key skillsets that will be required for all relevant tasks mentioned:

10 years of experience in system analysis, integration engineering, data engineering or technical delivery roles.

Strong ability to translate requirements into system flows, data flows, interface specifications and implementation plans.

Experience working with upstream and downstream teams to define and deliver enterprise integrations.

Practical experience with REST APIs, SFTP, batch processing, file based integration and data pipeline orchestration.

Good understanding of data mapping, transformation, aggregation, reconciliation and data quality controls.

Good SQL skills and basic to moderate Python skills for data handling, scripting, automation and troubleshooting.

Exposure to Java

Exposure to Informatica, Cloudera or similar enterprise data platforms.

Working knowledge of Git, branching, pull requests, code reviews and controlled release practices.

Familiarity with CI/CD, Jira, Confluence and enterprise deployment processes.

Experience with Control M or equivalent scheduling tools.

Familiarity with logging (OTEL) and monitoring tools such as Splunk Elastic Stack.

Exposure to GenAI concepts such as document ingestion, RAG, embeddings and data preparation for AI workflows.

Strong communication skills, with the ability to challenge weak designs and coordinate across business, application, data, infrastructure and security teams.

Key Domain:

Data Engineering,

System Integrations,

Python, SQL

About Encora

Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others.

At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality