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

1. 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

1. 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.

1. 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