Sr. Data Engineer

Overview

The Sr. Data Engineer will serve as a key technical contributor responsible for the design, development, and ongoing support of the company's enterprise data platform and business intelligence ecosystem. This role enables the organization to extract hidden insights from vast amounts of data—leveraging scalable ETL pipelines and cloud technologies—to empower smarter, faster decision‑making across the business.

This person will lead the development of scalable ETL/ELT pipelines using IICS (Informatica Intelligent Cloud Services) and AWS services (Lambda, Glue, Redshift, Bedrock, and Sage Maker). Working closely with Data Engineers, BI analysts, business stakeholders, and external consultants, this person will architect and evolve the data lake—ensuring data quality and integrity are maintained at all times. The Sr. Data Engineer must be a strong problem solver and multitasker who thrives managing multiple concurrent projects, resolves production bugs under pressure, and translates complex business needs into scalable technical solutions.

• Lead the design and development of ETL/ELT code to integrate data into the enterprise data lake using IICS and AWS Glue; mentor junior engineers and contribute to platform architecture decisions with direction from the Data Engineering Lead.
• Develop and maintain deep knowledge of the customer's business needs as they relate to data flows, data models, and BI consumption patterns.
• Support the integration of AI and machine learning capabilities into data workflows using AWS Bedrock and Sage Maker; ensure data pipelines are clean, well‑structured, and optimized for analytics and AI consumption.
• Design and implement AI‑ready data pipelines—ensuring data is clean, well‑structured, and optimized for downstream model training, inference, and analytics consumption.
• Collaborate with business process owners, external consultants, and the broader business community to define, understand, and prioritize demand for process and solution changes that optimize business value and BI delivery efficiency.
• Work closely with the Data Engineering Lead to estimate levels of effort for platform changes and partner with the business community to set priorities across multiple concurrent initiatives.
• Own the full delivery lifecycle: participate in requirements gathering; prepare requirements documents, functional and technical designs, test scenarios, and deployment plans.
• Manage and resolve all Data Engineering production support tickets; proactively triage and fix bugs in production pipelines, maintain SLAs, and report resolution progress to the business as requested.
• Leverage AWS services—including Lambda, Glue, Redshift, Bedrock, and Sage Maker—to build, optimize, and modernize data platform capabilities.
• Understand where data originates and how it is used across most process areas; ensure data lineage, quality, and integrity are maintained throughout the data lifecycle.
• Champion continuous improvement across data engineering practices, tooling, and documentation standards.
• May be required to perform other duties as assigned.

Required Education And Experience

• Education: or B.S. degree in Computer Information Systems, Computer Science, or related field.
• Experience: 6+ years of hands‑on experience in data engineering and ETL/ELT development is required. This includes strong proficiency in Python and GUI ETL tools such as IICS (Informatica Intelligent Cloud Services); and experience with AWS data services (Lambda, Glue, Redshift, Bedrock, Sage Maker). Candidates with fewer than 6 years of relevant experience will not be considered.

Required Skills

• Strong Python proficiency: ability to develop, analyze, debug, and optimize ETL pipelines, automation scripts, and data transformation logic end‑to‑end.
• Hands‑on experience with IICS (Informatica Intelligent Cloud Services) for enterprise‑scale ETL/ELT development, maintenance, and CI/CD pipeline integration.
• Deep AWS expertise across Lambda, Glue, Redshift, Bedrock, and Sage Maker; ability to architect and deploy cloud‑native data solutions.
• Experience working with generative AI services such as AWS Bedrock or Sage Maker…