Job Description

ROLE - Integration / Data Platform Specialist

Integration / Data Platform Specialist

Engagement - Contract: 1 month
Extendable based on performance and project requirements

Role objective

Support a data modernization assessment by evaluating integration and ingestion technologies against enterprise workload patterns. The role will focus on connectivity, data movement, orchestration, execution, operational fit and cloud data platform integration..

Preferred experience

- Data platform modernization programs.

- Informatica replacement or migration initiatives.

- Financial services or large enterprise environments.

- Experience assessing multiple integration technologies.

Requirements

Key responsibilities

- Assess enterprise integration and data ingestion patterns across relational, file and cloud-based sources.

- Evaluate connectivity across SQL databases, S3 and file-based interfaces.

- Assess Mule Soft and comparable integration patterns for batch, file, API and database workloads.

- Assess Snowflake Open Flow and related ingestion patterns for appropriate workload types.

- Analyse ETL versus ELT architecture considerations.

- Evaluate orchestration, scheduling, dependencies, routing and batch-processing requirements.

- Assess transformation, validation, exception handling, retry and recovery patterns.

- Review integration with Snowflake and implications for target architecture.

- Analyse runtime characteristics, execution windows, throughput and concurrency requirements.

- Assess monitoring, logging, alerting,



security and operational support considerations.

- Identify technology constraints, architectural dependencies and implementation considerations.

- Contribute to technology-to-workload mapping and modernization recommendations.

Required experience

- Strong experience in enterprise integration and data platforms.

- Hands-on Mule Soft / Anypoint Platform experience or comparable integration platform experience.

- Strong understanding of APIs, connectors, batch processing and orchestration.

- Experience with Snowflake and cloud data ingestion.

- Positive understanding of S3 and file-based ingestion patterns.

- Strong SQL and database integration knowledge.

- Understanding of ETL, ELT and contemporary data integration architectures.

- Familiarity with monitoring, retry, failure recovery and production operations

Benefits

What success looks like

Clear understanding of enterprise integration patterns, technically sound assessment of candidate platforms, and practical identification of where each technology can support modern data movement and integration requirements

Requirements
Key responsibilities Assess enterprise integration and data ingestion patterns across relational,



file and cloud-based sources. Evaluate connectivity across SQL databases, S3 and file-based interfaces. Assess Mule Soft and comparable integration patterns for batch, file, API and database workloads. Assess Snowflake Open Flow and related ingestion patterns for appropriate workload types. Analyse ETL versus ELT architecture considerations. Evaluate orchestration, scheduling, dependencies, routing and batch-processing requirements. Assess transformation, validation, exception handling, retry and recovery patterns. Review integration with Snowflake and implications for target architecture. Analyse runtime characteristics, execution windows, throughput and concurrency requirements. Assess monitoring, logging, alerting, security and operational support considerations. Identify technology constraints, architectural dependencies and implementation considerations. Contribute to technology-to-workload mapping and modernization recommendations. Required experience Strong experience in enterprise integration and data platforms. Hands-on Mule Soft / Anypoint Platform experience or comparable integration platform experience. Strong understanding of APIs, connectors, batch processing and orchestration. Experience with Snowflake and cloud data ingestion. Good understanding of S3 and file-based ingestion patterns. Strong SQL and database integration knowledge. Understanding of ETL, ELT and modern data integration architectures. Familiarity with monitoring, retry, failure recovery and production operations

📌 Integration / Data Platform Specialist Role (India)
🏢 Latent Bridge
📍 India