Engineering Data Analyst

Description

About Us:

US Conec is a global leader in the design, development, and manufacturing of high-density fiber optic connector solutions. With over 30 years of expertise in precision engineering, injection molding, and plastics manufacturing, we continue to drive innovation and redefine the optical interconnect industry. 

US Conec is a stable and growing organization with locations in Hickory, NC and Fort Worth, TX. What sets us apart from other employers? Our core values and company culture. We offer a collaborative team environment, a customer and employee centric work culture, and outstanding benefits that include a minimum of 4 weeks of PTO for all team members. 

About the job:

The Engineering Data Analyst will have broad experience working with cross functional teams to solve complex issues related to data visualization, data mapping, relationships, and overall system operation. The ideal candidate will implement data standards and deploy automation tools to extract, synthesize, and validate data from different sources and transform data into usable metrics. 

What you will do:

Data Collection and Cleaning:

• Utilize scripting and querying tools like Python, R or SQL, data visualization/BI tools, statistical methods, and data modeling to produce reports, data files, and dashboards. 

• Gather and compiles data from various sources to ensure comprehensive datasets.

• Clean and preprocess data to identify and rectify errors, missing information, or inconsistencies.

Data analysis (performed on an individual basis and / or at the direction of stakeholder):

• Performs exploratory data analysis to identify trends, patterns, and anomalies.

• Utilizes statistical methods to analyze large datasets and derive meaningful conclusions.

• Develops and implements data models, algorithms, and visualizations to highlight requirements from stakeholders.

• Identifies trends, patterns, and correlations in data to support strategic decision-making.

• Conducts thorough data validation, ensuring efficiency and data integrity.

Reporting and Visualization:

• Creates and maintains interactive dashboards and reports to communicate key findings.

• Collaborates with cross-functional teams to understand reporting requirements and deliver actionable insights.

Data Interpretation and Communication:

• Collaborate with stakeholders to understand their needs, requirements, and objectives.

• Translates complex data findings into understandable and actionable insights for non-technical stakeholders.

• Presents data-driven insights to inform engineering strategies and decision-making processes.

BI tool implementation:

• Implements business intelligence tools that align with organizational needs.

• Designs and develops dashboards, reports, and data visualizations at the direction of stakeholders.

• Ensures user-friendly interfaces and accessibility for non-technical stakeholders.

Works closely with other departments to understand their data needs and provide analytical support.

• Works closely with IT teams to ensure seamless data integration and system compatibility.

Performance Monitoring:

• Establishes and monitors key performance indicators (KPIs) to assess the effectiveness of BI solutions.

• Provides regular reports on BI tool performance and recommends improvements.

Training and Support:

• Conducts training sessions for end-users to promote self-service BI capabilities.

• Provides ongoing support to users, addressing issues, and enhancing their proficiency in using BI tools.

Requirements

What we'd like you to have:

• Bachelor's degree in a relevant field (e.g., statistics, mathematics, computer science).

• 1-3 years’ experience as a data analyst or a similar role.

• Strong proficiency in data analysis tools and programming languages (e.g., Python, R, SQL).

• Experience with data visualization tools (e.g., Tableau, Power BI).

• Solid understanding of statistical concepts and methods.

• Excellent communication skills with the ability to convey complex findings to non-technical stakeholders.

• Detail-oriented with a strong commitment to data accuracy and quality.

• Knowledge of data modeling and database design principles.

• Excellent analytical and problem-solving skills.

• Experience with ETL (extract, transform, load) processes and tools preferred.

• Familiarity with data warehousing concepts a plus.