Software Engineer - IICS

Pivotree

About The Position

Pivotree is seeking an IICS Developer to design, build, and support integration pipelines that collect, transform, and manage product and enterprise data across cloud applications, databases, and data platforms. The role develops and supports Informatica PowerCenter and Informatica Intelligent Cloud Services (IICS) solutions for enterprise data integration, including batch and near-real-time processing, cloud and on-premises integrations, data warehousing, and application integration. It also contributes to AI-enabled product data enrichment as project needs require. AI tools are used throughout day-to-day engineering work under standards for quality, data handling, validation, and review. The engineer must follow Pivotree’s AI usage policy, protect client and customer data, validate AI-suggested code and fixes against evidence, and record where AI contributed to changes. The role collaborates with data architects, business analysts, and cross-functional teams, documents reusable integration patterns, improves data management processes, and communicates project status to management and stakeholders.

Requirements

At least 3 years of hands-on IICS Cloud Data Integration (CDI) and Cloud Application Integration (CAI) experience, including mappings, mapping tasks, task flows, schedules, parameter files, transformations, CAI processes, service connectors, and process objects.
At least 5 years of hands-on Informatica PowerCenter experience, including mappings, workflows, reusable transformations, stored procedures, and session tuning.
Advanced SQL skills with Oracle and SQL Server, including complex joins, analytic functions, query tuning, and DDL generation.
Experience with REST APIs and web services using JSON and XML payloads, including authentication and error handling.
Experience with data warehousing and modeling, including star schemas, SCD Types 1 and 2, incremental loads, conceptual, logical, and physical data models, and data quality and lineage tooling.
Experience with flat-file processing, including CSV, delimited, and XML files; file-watching and SFTP transfer scripts; Unix/Linux shell or DOS scripting; and installing IICS add-on connectors and drivers.
Experience with version control and deployment, including Git, IICS asset management, and promotion across development, test, and production environments.
Working fluency with an approved AI assistant for SQL, mapping logic, scripts, and documentation; ability to verify AI output against sample data and execution plans, protect client data, and document AI contributions.
Ability to learn new technology quickly and adapt to changes in tools and platforms.
Strong analytical and troubleshooting skills and a systematic approach to root cause analysis.
Clear written and verbal communication with technical and non-technical audiences.
Commitment to documentation, reusable design patterns, and engineering best practices.
Ownership of quality, including willingness to challenge assumptions and validate AI-generated outputs before production.

Nice To Haves

Experience loading data into and tuning performance for Snowflake, Amazon Redshift, or Google BigQuery.
Python experience for validation and API work.
Experience building or supporting LLM-based pipeline steps such as enrichment or classification, including evaluation and cost monitoring.

Responsibilities

Design, develop, and maintain scalable, secure, and high-performance Informatica PowerCenter and IICS solutions.
Develop and optimize mappings, workflows, reusable transformations, expressions, stored procedures, and ETL pipelines for data warehouses, data lakes, and operational systems.
Build and support integration patterns for incremental and delta loads, SCD Types 1 and 2, star schema loads, and large-scale batch and near-real-time processing.
Build and maintain REST and web service integrations, service connectors, business services, and IICS Application Integration processes and process objects for real-time integrations.
Install and configure IICS add-on connectors and drivers; build file-watching and file-transfer scripts for scheduled and event-driven data exchange.
Optimize SQL performance, database connectivity, task scheduling, and cloud-native deployments on Snowflake, Amazon Redshift, and Google BigQuery; validate AI-generated recommendations against execution plans and load metrics.
Implement data quality checks, governance controls, metadata management, lineage, and impact analysis.
Troubleshoot ETL, integration, and pipeline issues, including using AI-assisted root cause analysis; validate suggested fixes against logs, sample data, and execution plans before production.
Use approved AI tools to draft and review mapping logic, SQL, test data, and documentation, and to summarize job logs; comply with AI-use and data-handling policies and record AI contributions.
Contribute to AI-enabled data enrichment use cases, including attribute extraction, categorization, and content normalization for PIM, as required by the project roadmap.
Collaborate with data architects, business analysts, and cross-functional teams on integration architectures, reusable patterns, guidelines, and data management improvements.
Communicate project status clearly to management and stakeholders.