Data Engineer

Job Title: Data Engineer

Location-Type: Remote (CST)

Start Date Is: ASAP

Duration: 6-month contract with potential to convert to FTE

Compensation Range: $35-45/hr W2

Role Overview: We are seeking a skilled Sr. Data Engineer to join our client’s Commercial Team. In this role, you will collaborate with stakeholders to design, build, and maintain data infrastructure that supports the commercial team's efforts. This role focuses on enabling seamless data flow, analysis, and reporting, ensuring that data drives business decisions and growth.

Day-to-Day Responsibilities:
• Integrate various data sources to create a unified view of key business data (revenue, orders, pipeline, marketing, customer).
• Develop efficient data models for business reporting and decision-making using SQL, Python, or R.
• Work closely with data scientists and analysts to ensure data quality and integrity.
• Design and maintain a commercial data dictionary for clear data element definitions.
• Build and optimize Power BI data models and dashboards for reporting and analytics.
• Collaborate with business analysts to translate business needs into technical data models and visualizations.
• Automate data processing tasks to improve operational efficiency.
• Develop scalable data pipelines to support real-time analytics and reporting.

Must-Haves:
• 3+ years of experience in data engineering, with a focus on building data models and managing data dictionaries.
• Proficiency with Power BI, including building complex models and dashboards with DAX/PowerQuery.
• Experience with Snowflake data models and architecture.
• Strong SQL skills for data querying, manipulation, and ETL processes.
• Experience with CRM systems (e.g., Salesforce) and sales performance data.
• Bachelor's or Master’s degree in Computer Science, Data Engineering, Information Systems, or related field.
• Expertise in statistical and mathematical methodologies for data analysis.
• Exceptional project management and organizational skills.
• Strong communication skills to convey technical data insights to non-technical audiences.

Nice-to-Haves:
• Familiarity with automated data processing tools and techniques.
• Knowledge of advanced data modeling and visualization techniques.