Senior Data Engineer

Potential with Quanex•Houston, TX

5d•Onsite

About The Position

Quanex is looking for a Sr. Data Engineer to join our team located in Houston, Texas. The Sr. Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and architectures that support enterprise reporting, analytics, and integration needs. This role ensures reliable, high-quality data flows across systems and owns the full data lifecycle—from ingestion to transformation, storage, and consumption—enabling business insights and data-driven decision-making.

Requirements

5+ years of experience in data engineering or related roles.
Bachelor’s degree in computer science, Information Technology, Data Science, Engineering, or a related technical field required.
Advanced SQL expertise (complex joins, window functions, query optimization, indexing strategies, performance tuning).
Strong experience with ETL/ELT tools and frameworks.
Deep understanding of data lifecycle management (ingestion, transformation, storage, governance, and consumption).
Strong experience with data integration patterns (APIs, batch processing, streaming, middleware).
Proficiency in data modeling (star/snowflake schemas, normalization vs denormalization).
Experience with Data Warehousing and Data Lake architectures.
Experience with cloud platforms (Azure preferred).
Experience with Microsoft Fabric, Azure Data Factory, or similar tools.
Familiarity with ERP systems (SAP, Oracle, NetSuite).
Experience with financial data and reconciliation processes.
Exposure to big data technologies (Spark, Databricks).
Understanding of EDI or structured data exchange formats.
Experience implementing data governance and data quality frameworks.
Strong analytical and problem-solving skills.
Attention to detail with strong focus on data quality and integrity.
Ability to understand and manage end-to-end data flows across systems.
Strong collaboration across technical and business teams.
Ownership mindset with proactive issue resolution.
Ability to work in agile, fast-paced environments.

Responsibilities

Design, build, and maintain ETL/ELT pipelines to ingest data from ERPs, applications, APIs, and external sources.
Own and manage the full data lifecycle: ingestion, transformation, storage, modeling, and consumption.
Develop and optimize complex SQL queries, stored procedures, and data transformations for large-scale datasets.
Design and maintain scalable data models for Data Warehouse and Data Lake environments (star/snowflake schemas).
Integrate data across multiple systems (ERPs, APIs, flat files, third-party tools) ensuring consistency and reliability.
Collaborate with integration teams to align data pipelines with enterprise architecture (integration layers, APIs, middleware).
Implement data quality, validation, and monitoring frameworks across all stages of the data lifecycle.
Optimize data pipelines, queries, and storage for performance, scalability, and cost efficiency.
Troubleshoot data issues and ensure timely resolution of data-related incidents.
Partner with BI developers, analysts, and business stakeholders to deliver high-quality data solutions.