Data Engineer

Summary

Join Apiphani, a technology-enabled managed services company, as a Data Engineer. You will design, develop, test, and deploy data pipelines, warehouses, lakes, and products. Collaborate with data analysts, scientists, and stakeholders to ensure data quality and reliability. Develop and configure programs for data ingestion, transformation, and enhancement. Align data systems with business goals and strive for efficiency. This role requires strong data analysis skills and experience with various programming languages. Machine learning knowledge is a plus.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field, or equivalent work experience
• 3+ years of experience in data engineering or related roles
• Proficient in SQL and at least one programming language such as Python, etc
• Experience with data pipeline orchestration and scheduling tools such as AWS Glue, Lambda, etc
• Experience with cloud-based data platforms and services in AWS. Azure, or GCP are a plus
• Experience with data warehouse and data lake design and architecture
• Experience with data quality, data testing, and data governance methodologies and tools
• Strong analytical and problem-solving skills, attention to detail, and communication skills
• Ability to work independently and collaboratively in a fast-paced environment

Responsibilities

• Design, build, and optimize data pipelines using various tools and technologies such as SQL, Python, AppFlow, Glue, etc
• Implement data quality checks, data validation, and data governance processes to ensure data accuracy and consistency
• Develop and maintain data models, schemas, and metadata to support data analysis and reporting
• Create and manage data warehouses, data lakes, and data marts using cloud platforms such as AWS, Azure, or GCP
• Collaborate with data analysts, data scientists, and other business users to understand their data needs and provide data solutions
• Collaborate with technical, including DevOps, engineering, and compliance, to ensure seamless cloud implementation and adherence to best practices
• Develop data and cloud architecture documentation, including diagrams, guidelines, and best practices for reference and knowledge sharing
• Troubleshoot and resolve data pipeline issues, ensuring minimal downtime and data integrity
• Optimize data pipelines for performance, reliability, and data quality, utilizing best practices in data engineering
• Build algorithms and prototypes that combine raw information from different sources
• Document solutions and provide DataOps support for production data pipelines

Preferred Qualifications

• Experience working with a modern data catalog such as Alation, Collibra, etc. is a plus
• Ability to prepare data for prescriptive and predictive modeling is a plus
• Experience working with AI technologies such as Amazon Q is a plus

Benefits

• Medical/dental/vision - 100% paid for employees, 50% paid for dependents
• Life and disability - 100% paid for employees
• 401K - 3% match, no employee contribution necessary
• Education and tuition reimbursement - up to $50K annually
• Employee Stock Options Plan
• Accident, critical illness, hospital indemnity benefits offered through our providers
• Employee Assistance Program
• Legal assistance
• Unlimited PTO