Senior Data Platform Engineer

About Sovrn

Every interesting company solves essential problems for other people. Sovrn is a Software and Data business that helps Open Web businesses remain independent. We help them understand their business better, operate more efficiently, and make and keep more money.

• We believe in the freedom and free flow of information.
• We believe the Open Web is the largest source of this information.
• We believe in helping Open Web businesses be and remain Independent.

Through Software products and Data solutions, we help our customers:

• Understand their business better, so they can make better decisions.
• Operate their business more efficiently, so they can invest in what matters most.
• Make (and Keep) more money, so they control their own destiny.

About the Team

Our team focuses on the maintenance, evolution and engineering of the data platform as well as data processing across Sovrn’s Data Collective. We focus on the architecture, transformation, availability, governance and evolution of data, so that critical product insights are readily obtainable by Sovrn’s internal business leaders. Additionally, we focus on key data technology solutions and serve as subject matter experts on our ETL, data warehousing and business intelligence tools. The team drives collaboration between engineers, data scientists, business analysts and product managers to enable better data access across all of our product lines. 

About the Job

As a Senior Data Platform Engineer, you will collaborate with cross-functional teams to enhance our data architectureI, troubleshoot data processing issues, and implement solutions to ensure the integrity, efficiency, and governance of our data ecosystem. The ideal candidate is passionate about building and maintaining key datasets and data infrastructure, possesses strong problem-solving skills, and has a proven track record in managing and optimizing data platforms. 

What You’ll Be Doing:

• Perform architecture design, table design, metric consistency, data modeling, and implementation of a big data platform and analytics applications.
• Analyze latest big data and analytics technologies and provide expertise in big data strategies.
• Provide governance of business-critical product data sets within Sovrn’s data warehouse and ensure their readiness for data analysts and other internal business users.
• Specify data platform components and configurations required for data pipeline implementation.
• Implement data pipeline metrics to monitor performance, accuracy, and availability.
• Research, implement, and evolve methods to process our data.
• Optimize data processing and data access to business intelligence tools.
• Provide domain expertise across the organization to enable business growth and development through data services and data models.
• Troubleshoot systemic issues and lead improvements.
• Work with the security team to implement and maintain robust data security measures.
• Ensure compliance with relevant data governance and privacy regulations.

About You

You share Sovrn’s belief that a highly effective engineer is defined as much more than just technical ability, but also someone who uses exceptional interpersonal skills to improve team dynamics and executes on technical work with a long-term strategic vision. You are a self starter and able to get the job done without direct supervision. You enjoy leading a collaborative team but are also independently responsible. You are technically curious and enjoy investigating what is possible. Defining technical challenges and solving problems with your team to make better software gets you excited.

The successful candidate will have:

• Excellent understanding of big data processing environments such as Spark and Databricks.
• Hands-on experience with data processing using Spark and Python.
• Hands-on experience in big data and distributed data processing in the AWS ecosystem.
• Hands-on experience with orchestration tools such as Airflow and MWAA.
• Proficiency with Postgres, Athena, and DynamoDB. 
• Experience with data warehousing and data mart design and implementation.
• Strong understanding and inner workings of metadata management, data lineage, and data governance.
• Strong experience in structured, unstructured, semi-structured data techniques and processes.
• Hands on experience with infrastructure as code tools like Terraform and AWS Cloudformation.
• Ability to clearly document and communicate architectural concepts at multiple levels.
• Experience with data security and compliance (PII, CCPA