Data & Integration Engineer (GenAI)

We are looking for a Data & Integration Engineer who operates effectively at the intersection of system analysis, enterprise integration and data engineering to support GenAI initiatives.

The successful candidate will:

Understand business and functional requirements

Translate them into data flows and integration designs

Work across upstream and downstream systems

Ensure reliable movement, transformation and availability of data for GenAI use cases

Develop scripts / programs to get data from different integration systems

Develop APIs to integrated with relevant systems.

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

Support data ingestion and preparation for GenAI use cases

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

Design and implement data movement across systems using:

APIs

SFTP and file based transfers

Batch pipelines

Requirements

Key Requirements

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

Good 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.

Working experience with Informatica is preferable.

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

Data Engineering,

System Integrations,

Python, SQL, Informatica