Data Engineer

Job Title: Data Engineer Location: Riverdale, UT Employment Type: Contract to Hire Pay: $40-47/hr Overview We are seeking a Data Engineer to design, build, and maintain scalable data pipelines and solutions that support advanced analytics and data science initiatives. This role involves working with cloud technologies, real-time systems, and modern data engineering practices to ensure data integrity, security, and performance. Responsibilities • Serve as the primary contact for data pipelines, supporting operational implementation of Data Science and analytical models. • Engineer solutions using serverless technology for optimal performance and scalability. • Develop and adapt analytics solution engineering strategies and requirements. • Perform DevOps tasks and orchestrate data marts and analytical processes. • Monitor, secure, and track data usage and analytic product performance. • Collaborate with internal teams to deliver accurate, accessible API services. • Ensure compliance with security, documentation, governance, and standards. • Manage a reporting layer to provide insights into model performance and impact. • Identify potential issues based on trend projections and system monitoring. • Participate in daily stand-ups, troubleshoot overnight pipeline runs, and integrate new data sources into the data warehouse. • Perform data cleaning and transformation using SQL and Python. • Design and implement data models, optimize database performance, and build scalable pipelines using cloud platforms. • Document data processes and infrastructure changes. • Respond to ad-hoc data requests and provide insights for decision-making. Required Skills & Experience • 2–4 years of experience designing, developing, and implementing Data Science solutions. • Advanced programming experience in Python. • Experience building data pipelines with Airflow. • Advanced database skills (MSSQL, Oracle, Postgres). • Familiarity with Kubernetes and Linux environments. • Ability to obtain a U.S. Security Clearance. • Bachelor’s degree in a related field. • Experience with Kafka (a strong plus). Nice to Have • Experience working in the financial industry. • Master’s degree in a related field.