Data Analytics Engineer

Haynes International is seeking a Data Analytics Engineer to join onsite in Kokomo, IN.

Responsibilities

• Delivers clearly defined, validated data assets ready for analysis, with documentation and code reviews.
• Builds data aggregation pipelines leveraging SQL, .NET, Targit, and Power BI.
• Designs scalable data models and architectures to support analytics initiatives.
• Collaborates with business stakeholders to translate analytics needs into reports, dashboards, and data models.
• Identifies optimization opportunities to boost query performance, shorten processing times, and improve overall productivity.
• Designs, builds, and maintains data pipelines to ensure efficient and reliable ETL operations.
• Implements and maintains analytics platforms, including data warehouses or data lakes, to store and manage structured and unstructured data.
• Creates and maintains dashboards, visualizations, and reports using Targit and Power BI to support data-driven decision-making.
• Partners with the Data Analytics Manager to embed Power BI usage and data governance across the organization.
• Ensures data quality and accuracy through validation, monitoring, and robust error-handling processes.

Requirements

• Bachelor’s degree in computer science, data science, software engineering, or a related field (R).
• Minimum five years of experience in data analytics, data engineering, software engineering, or a related role (R).
• Expertise in data modeling, ETL development, and data analysis (R).
• Proficiency in SQL for data extraction and manipulation; experience with data warehousing concepts and tools such as Targit, Ignite, and Power BI; familiarity with Azure cloud-based data platforms; programming ability in C++ and .NET for data manipulation and scripting; solid understanding of data governance, data quality, and data security best practices; strong problem-solving skills.

Technologies

• SQL
• Targit
• Ignite
• Power BI
• Azure
• C++
• .NET

About the Opportunity

The analytics engineer ensures data is ingested, transformed, scheduled, and prepared for analytics. This role designs and maintains data pipelines, analytics systems, and reporting solutions, converting raw data into clean, reusable datasets that enable business stakeholders to view and understand data within a data warehouse or database.