Data Engineer

Requirements

• Education : Bachelor's degree in computer science, data science, technology, information systems or engineering preferred.
• Experience : 3-5 years of professional experience in data, analytics, or platform engineering or related work-related experience strongly preferred.
• Here's a little bit about us:
• Benefits: In addition to core benefits like health, dental and vision, also enjoy benefits such as:
• Paid Parental Leave and supportive New Parent Benefits - We know being a working parent is hard, and we want to support our employees in this journey!
• Company paid continuing Education & Tuition Reimbursement - We support those who want to develop and grow.
• Generous time off practices in addition to paid holidays - Yes, we actually encourage employees to use their time off, and they do. After all, you can't be at your best for our clients if you're not at your best for yourself first.
• Supportive of community efforts with paid Volunteer time off and employee matching gifts to charities that are important to you - Through our Holmes Murphy Foundation, we offer several vehicles where you can make an impact and care for those around you.
• Consistent merit increase and promotion opportunities - Annually, employees are reviewed for merit increases and promotion opportunities because we believe growth is important - not only with your financial wellbeing, but also your career wellbeing.
• Discretionary bonus opportunity - Yes, there is an annual opportunity to make more money. Who doesn't love that?!
• Holmes Murphy & Associates is an Equal Opportunity Employer.

Benefits

Additional Information

Job Description: We are looking to add a Data Engineer to join our Information Technology team in West Des Moines, IA . Offering a forward-thinking, innovative, and vibrant company culture, along with the opportunity to share your unique potential, there really is no place like Holmes! Essential Responsibilities: Design and Implement Complex Pipelines: Design, build, and optimize ETL/ELT workflows from multiple sources, enhancing performance and reliability. Azure Data Factory, Alteryx, Fabric, dbt, SQL, and other tools. Advanced Data Transformations: Implement transformations, aggregations, and custom logic to meet business requirements. Data Modeling and Storage Optimization: Contribute to data modeling efforts, recommending storage solutions and structures that support analytical requirements. Pipeline Monitoring and Optimization: Proactively monitor pipelines, perform root cause analysis for performance issues, and implement improvements. Mentorship and Guidance: Provide guidance to junior engineers on best practices in data extraction, transformation, and loading.

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