Data Platform Engineer

As a Data Platform Engineer your core responsibility revolves around crafting, advancing, and maintaining the infrastructure and systems essential for managing and optimizing data as an enterprise asset. In this capacity, you will create and maintain tooling, abstractions, and services that allow enterprise users to meticulously oversee the entire lifecycle of their data product, encompassing the efficient collection, storage, processing, and retrieval of data, all while upholding stringent standards for security, governance, and data quality. You will possess extensive expertise in working with diverse data storage technologies, including databases, data lakes, and data warehouses, as well as streaming architectures and service layer technologies. You are proficient in programming languages such as Python, Scala, Java, and SQL. Your skillset extends to encompass data integration, ETL (Extract, Transform, Load) processes, ELT (Extract, Load, Transform), Restful/GRPC services, Streaming, and the construction and abstraction of robust data pipelines. The overarching objective as a Data Platform Engineer is to enable enterprise product teams to deliver quality data products that drive business insight and value to our customers. This includes building tooling and services that connects data sources to data consumers and ensures the accessibility, structural integrity, and reliability of data to fulfill analytical and business imperatives.
PRIMARY ACCOUNTABILITIES

Collaborate with data platform architects to design and specify platform 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

KNOWLEDGE, SKILLS AND ABILITIES

7+ years 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, Scala, or Java
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
Must know standard practices of the Software Development Lifecycle (SDLC)
Must have proficiency in standard SDLC concepts and tooling including unit and integration testing frameworks like Pytest, IDE features like debugging, testing practices like mocking, CICD tooling like Github actions, build tooling (poetry), GIT
Must have proficiency in creating and using basic Restful or GRPC services
Must have proficiency in message bus and streaming technologies and understand common event stream architectures
Knowledge of the health care industry is a plus

Job Types: Full-time, Contract
Pay: $64.55 - $68.25 per hour
Schedule:

8 hour shift

Ability to Commute:

Minneapolis, MN 55401 (Required)

Ability to Relocate:

Minneapolis, MN 55401: Relocate before starting work (Required)

Work Location: In person