Data Platform Engineer: Lakes, Streaming & Governance

Clinician Nexus; United States; On-site; USD 120,000 - 190,000; Full time

Job summary

Clinician Nexus is hiring a Data Platform Engineer to design, implement, and maintain scalable data infrastructure. You will build data lakes and lake houses, create streaming and batch pipelines, and integrate them with software products across teams.

The role requires strong Python expertise, Spark proficiency, and experience with ELT/ETL in distributed compute environments, preferably Databricks, while mentoring junior engineers and upholding data governance and quality standards.

Qualifications

• 5+ years of relevant experience.
• Degree in Computer Science, Software Engineering, Information Systems, Information Technology or a related computer degree or equivalent experience.
• Master's degree is a plus
• Must know and have proficiency in one object or object/functional programing language. Preferably Python
• Must know common object and object/functional design patterns. Builder, factory, façade, context, etc.
• Must have proficiency with Apache Spark
• Must know data lake and lake house design principles, OLTP (Online Transaction Processing) design principles, document data stores, and graph
• Must know and understand how to build ELT/ETL patterns in a distributed compute system. Preferably Databricks
• Must know and have proficiency with common data quality tooling and the design of configurable systems to front end that tooling
• Must know and have proficiency with common systems and data observability tooling

Responsibilities

• Collaborate with data platform architects to design tooling, services, and integrations.
• Build data lake and lake house architectures.
• Build streaming data architectures to support data platform tooling and services.
• Collaborate with software teams to integrate streaming and batch architectures with software products.
• Collaborate with data scientists, analysts, and business stakeholders to MVP optimal solutions.
• Collaborate with data governance teams and data platform architects to build governance into technical solutions.
• Maintain systems and services that provide transparency and observability into our critical systems.
• Implement and promote engineering and architectural patterns, perform code reviews, and collaborate in architectural reviews.
• Collaborate with product team data engineers and architects to MVP data products, maintain data models, and promote data modeling best practice.
• Provide technical leadership and mentorship to product and data engineers, guiding their growth and professional development and enabling their ability to use platform tooling and services.
• Lead by example through hands-on contributions to designing, coding, and troubleshooting complex data systems.
• Identify and address performance bottlenecks and optimization opportunities within data pipelines, databases, and processing frameworks.
• Optimize data processing workflows to improve efficiency and reduce latency.
• Lead efforts to diagnose and resolve data-related incidents in a timely manner.
• Will participate in the grooming of stories
• Will be responsible for their own tasking towards the completion of stories
• Will mentor junior members of the team and guide junior members on best practice
• Will participate in design
• Will be responsible for the quality of their own code and will participate in code review of others product
• Will be responsible for integrating their own code with the team's DevOps plan and implementation

Skills

Python

Software design patterns

Apache Spark

Data lake / lake house

ETL/ELT patterns

Data quality tooling

Observability tooling

Education

Bachelor's degree in Computer Science, Software Engineering, Information Systems, Information Technology or related

Master's degree is a plus

Tools

Databricks

SQL

Java

Scala

Job description

Clinician Nexus is hiring a Data Platform Engineer to design, implement, and maintain scalable data infrastructure. You will build data lakes and lake houses, create streaming and batch pipelines, and integrate them with software products across teams.

The role requires strong Python expertise, Spark proficiency, and experience with ELT/ETL in distributed compute environments, preferably Databricks, while mentoring junior engineers and upholding data governance and quality standards.