Data Engineer

Data Engineer - Austin, TX

About Nomi Health

Nomi Health is revolutionizing healthcare access through innovative technology. We are seeking a talented Data Engineer to join our growing team in Austin, Texas.

Job Description

As a Data Engineer, you will play a crucial role in designing, implementing, and maintaining our data pipelines. You will ensure seamless integration of data from diverse sources into our platform, guaranteeing data accessibility, cleanliness, and optimization.

Responsibilities:

• Design, implement, and maintain efficient ETL pipelines for data integration.
• Support automated processes for complex data analysis, management, and visualizations, incorporating data governance best practices.
• Make informed decisions on complex data issues, including technical approach for project components and reporting requirements.
• Design and implement data model changes aligned with Nomi's standards.
• Develop and execute comprehensive testing strategies to ensure high data quality.
• Collaborate effectively with cross-functional teams to achieve shared goals.

Qualifications:

• 2+ years of experience in data engineering or a related field.
• Proficiency in NoSQL and SQL (Snowflake).
• Experience with AWS resources (lambdas, docDB, EC2) is preferred.
• Strong understanding of data warehousing principles and best practices.
• Experience with Python, Git, and Jira.
• Experience handling sensitive data is a plus.

Benefits:

• Competitive salary and benefits package.
• Opportunity to work on cutting-edge technology in a fast-paced environment.
• Collaborative and supportive team culture.

Qualifications

Required:

• 2+ years of experience in data engineering or a related field.
• Proficiency in SQL (Snowflake) and NoSQL databases.
• Experience with Python programming language.
• Familiarity with Git for version control and Jira for project management.
• Strong understanding of data modeling principles and best practices.
• Demonstrated ability to design, implement, and maintain efficient data pipelines (ETLs).
• Commitment to data quality and implementing robust testing strategies.
• Excellent communication and collaboration skills to effectively work with cross-functional teams.

Preferred:

• Experience with AWS resources such as Lambda, DocDB, and EC2.
• Experience handling sensitive data and adhering to data governance policies.

Key Responsibilities

Data Pipeline Development & Maintenance:

• Design, build, and maintain efficient data pipelines (ETLs) to integrate diverse data sources into the Nomi platform.
• Ensure data quality, accuracy, and consistency throughout the pipeline process.
• Optimize pipeline performance and scalability to handle growing data volumes.

Data Governance & Analysis:

• Support the implementation of automated processes for complex data analysis, management, and visualization.
• Adhere to data governance policies and best practices to ensure data security and compliance.
• Collaborate with stakeholders to define reporting requirements and develop insightful data-driven reports.

Data Modeling & Quality Assurance:

• Design and implement data model changes that align with Nomi's standards and evolving business needs.
• Develop and execute comprehensive testing strategies to guarantee high data quality and integrity.
• Identify and resolve data quality issues proactively.

Team Collaboration & Communication:

• Work closely with cross-functional teams (e.g., engineering, product, analytics) to understand data requirements and deliver solutions.
• Effectively communicate technical concepts and data insights to both technical and non-technical audiences.

Nomi Health Data Engineer Hiring Workflow

1. Application Review: Candidates submit resumes and cover letters through the job portal. The AI agent automatically screens applications based on keywords and qualifications, prioritizing those with relevant experience in data engineering, SQL, NoSQL, and AWS.

2. Skills Assessment: Shortlisted candidates complete a technical assessment testing their proficiency in SQL, Python, and data pipeline concepts.

3. Phone Screening: A recruiter conducts a phone interview to assess communication skills, cultural fit, and delve deeper into the candidate's experience.

4. Technical Interview: A panel of engineers interviews candidates, focusing on their technical skills, problem-solving abilities, and understanding of data engineering principles.

5. Case Study: Candidates are presented with a realistic data engineering challenge relevant to Nomi Health's platform. They are expected to propose solutions and discuss their approach.

6. Final Interview: The top candidates meet with senior leadership to discuss their career goals, alignment with Nomi Health's vision, and potential contributions to the team.

7. Decision & Offer: The hiring team reviews all interview feedback and makes a final decision. A competitive offer is extended to the selected candidate.

About Nomi Health

Nomi Health is revolutionizing healthcare by simplifying access to quality care. We build innovative technology solutions that connect patients with providers, streamline administrative processes, and empower individuals to take control of their health journey.

Driven by a mission to make healthcare more accessible and affordable, Nomi Health leverages data-driven insights to create a seamless and personalized experience for everyone. Our team of passionate individuals is dedicated to building a future where healthcare is truly patient-centric.