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