Data Engineer

Job Overview

• Balance: We understand the importance of a healthy work-life balance. At HODGE, you can count on having holidays off (while still getting paid for them), allowing you to spend quality time with your family and friends.
• Great Benefits: We value our employees' well-being and offer a comprehensive benefits package. Enjoy paid time off, 401k, medical, dental, and vision insurance, life insurance, an employee assistance program, wellness program, and much more!
• Competitive Pay: We offer competitive wages. Your hard work will be recognized and rewarded!
• Safety First: At HODGE, we prioritize safety above all else. Your well-being is our top priority. We protect our work family by maintaining safety policies, including the use of personal protective equipment (PPE) and proactive hazard identification.
• Ambition: We're a team of ambitious individuals who are dedicated to achieving great things together. We embrace the "Whatever It Takes" mindset, ensuring that we go the extra mile to deliver exceptional results.
• Friendly Work Environment: Join a team that feels like family! You'll be supported by colleagues who genuinely care about your success and well-being.

• ETL & Data Modeling: Build and optimize ETL (extract, transform, load) processes for data transformation, ensuring timely and efficient data delivery to support advanced analytics and reporting.
• Partner in Building Key Performance Indicators (KPIs): Develop and implement KPIs to assess performance and efficiency, regularly evaluating progress against operational goals. Create sustainable analytical processes by documenting the development of each reporting tool and focus on sustainability.
• Data Pipeline Development: Ability to build, develop, design data architectures and maintain robust and scalable data pipelines to collect, process, and store data from various sources, ensuring data accuracy and consistency.
• Conduct Data Analysis and Performance Assessments: Leverage data-driven insights and analytics to identify inefficiencies and implement data-based solutions for optimization.
• Collaborate with Cross-Functional Teams: Work closely with teams across HODGE to understand data requirements and deliver data solutions that meet business needs.
• Data Quality and Governance: Implement data quality checks, validation procedures, and data governance practices to maintain high data integrity.
• Performance Tuning: Continuously monitor and optimize the performance of data pipelines and databases to ensure optimal data processing and storage.
• Security and Compliance: Implement and maintain data security best practices and ensure compliance with data privacy regulations.
• Mentorship: Provide guidance and mentorship to stakeholders and peers, fostering a culture of knowledge sharing and continuous improvement.
• Continuous Learning: A commitment to staying updated with the latest trends and technologies in data engineering and analytics.
• Demonstrate HODGE Values: Model core values of Family, Integrity, Ambition, Respect, and Balance. Uphold, support, and promote all company policies and procedures. Remember that success comes from treating people like family.

• Bachelor's or master's degree in computer science, Engineering, a related field, or equivalent work experience.
• Expertise in Data Technologies: Proficiency in technologies such as SQL, Python, Spark, Hadoop, Kafka, and cloud platforms (e.g., AWS, Azure, GCP).
• Database Management: Extensive experience with relational databases (e.g., PostgreSQL, MySQL).
• ETL Tools: Demonstrated proficiency in ETL tools and frameworks.
• Data Modeling: Strong knowledge of data modeling techniques and best practices.
• Data Quality: Experience implementing data quality checks and governance processes.
• Experience mining, integrating, and analyzing data from various systems such as SAP, AWS, Microsoft Azure, timekeeping systems, SharePoint, and/or other database systems or APIs.
• Communication: Effective communication skills to collaborate with cross-functional teams and convey technical concepts to non-technical stakeholders.
• Business Acumen: Ability to translate business needs into technical solutions and prioritize data work based on business impact.

• Cloud Infrastructure & DevOps: Understanding of infrastructure-as-code, containerization (e.g., Docker), and CI/CD pipelines.
• Proven analytical skills and experience with data analysis tools, such as Excel, Tableau, Power BI or similar platforms.
• Version Control: Familiarity with version control systems (e.g., Git).
• 2+ years' experience, preferably in warehouse or manufacturing industries
• Experience building tools that enable data driven decisions across company layers and improve business outcomes