Data Engineer - Data Platform
Overview
IntePros is seeking a Data Engineer to support a high-end fashion retailer's data engineering organization and help modernize and improve the reliability of a complex, business-critical data platform. The organization works with a broad range of data spanning operations, marketing, finance, accounting, e-commerce, and analytics, providing an opportunity to work with diverse datasets and solve meaningful business problems.
This role will focus heavily on modernizing and optimizing legacy Informatica data pipelines while helping transition workloads to a modern, AWS-based data platform. The ideal candidate has strong Informatica workflow design and implementation experience, solid AWS data engineering skills, and a proactive approach to identifying and resolving reliability, performance, and scalability issues.
The role is onsite in New York City and will work closely with a small data engineering team and business stakeholders across the organization. This is an excellent opportunity for someone who enjoys solving complex data problems, improving inefficient systems, and working across a wide variety of business domains.
Key Responsibilities

• Design, develop, and maintain scalable data pipelines and BI solutions using Informatica and AWS-based technologies.
• Modernize legacy Informatica workflows by migrating appropriate workloads to AWS and improving overall platform reliability.
• Analyze complex, fragile, and inefficient data pipelines to identify bottlenecks, failure points, and opportunities for simplification.
• Optimize existing workflows by reducing unnecessary processing steps, improving performance, and increasing reliability.
• Build and optimize ETL processes to improve data quality, freshness, accuracy, and availability.
• Develop data solutions using AWS services such as Glue, Lambda, EventBridge, and S3.
• Partner with business stakeholders across operations, marketing, finance, accounting, and other functions to understand requirements and translate them into scalable data solutions.
• Collaborate with data science teams to establish data foundations that support AI and machine learning initiatives.
• Monitor production pipelines, troubleshoot errors, and proactively identify issues before they impact downstream customers.
• Improve operational excellence through monitoring, automation, documentation, and process improvements.
• Participate in the design and implementation of new data products and capabilities as the data platform evolves.
• Leverage AI-powered development and data tools to improve productivity, code quality, and engineering effectiveness.

Required Qualifications

• 3-5 years of professional experience in data engineering, data integration, or a related technical field.
• Hands-on experience with Informatica workflow design, development, and implementation.
• Experience designing, developing, and troubleshooting complex ETL/data pipelines.
• Experience identifying and resolving data pipeline reliability, performance, and scalability issues.
• Strong understanding of data engineering concepts, including ETL, data quality, data dependencies, and pipeline orchestration.
• Experience working with cloud-based data platforms, preferably AWS.
• Strong analytical and problem-solving skills with the ability to break down complex technical problems.
• Ability to proactively identify issues and improve existing systems rather than simply maintaining the status quo.
• Strong communication skills with the ability to clearly articulate technical concepts and collaborate with both technical and non-technical stakeholders.
• Ability and willingness to work onsite in New York City.

Preferred Qualifications

• Hands-on experience with AWS data engineering services, particularly AWS Glue, Lambda, EventBridge, and S3.
• Experience with Databricks and/or Snowflake.
• Experience with Apache Airflow or other workflow orchestration tools.
• Experience modernizing legacy data platforms or migrating traditional ETL workflows to cloud-based architectures.
• Experience supporting data platforms used across multiple business functions.
• Experience partnering with data science teams to support AI/ML solutions.
• Experience simplifying and optimizing highly complex legacy pipelines.
• Strong sense of ownership, energy, curiosity, and willingness to take initiative in ambiguous environments.

Top Skills

1. Informatica & ETL Development - Strong hands-on experience designing, implementing, troubleshooting, and optimizing Informatica workflows and complex ETL pipelines.
2. AWS Data Engineering - Experience building and modernizing data pipelines using AWS services such as Glue, Lambda, EventBridge, and S3.
3. Data Pipeline Optimization & Reliability - Ability to analyze complicated legacy workflows, identify unnecessary complexity and failure points, and redesign pipelines for improved reliability, efficiency, and scalability.

Success Profile
Successful candidates are proactive data engineers who enjoy untangling complex systems and making them better. This role is particularly well suited for someone who can look at a legacy pipeline with dozens of unnecessary steps, understand why it is fragile, and develop a simpler, more reliable solution.
The ideal candidate is technically strong, curious, energetic, and comfortable taking ownership of problems before they become larger issues. They should be able to work effectively with a wide range of stakeholders and communicate technical concepts clearly. Someone who enjoys working with diverse datasets, solving challenging data problems, and modernizing legacy technology will thrive in this environment.

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