Staff Data Engineer - Remote

Overview

Later is the enterprise leader in social media and influencer marketing software, services, and data, trusted by leading brands and agencies worldwide. Following our acquisition of Mavely, the Everyday Influencer Platform®, Later enables brands to scale creator partnerships from nano to premium influencers while managing social media content and campaigns across all major social and affiliate networks. Through proprietary performance data, marketing leaders can drive attributable sales and optimize social commerce with our software platform or award-winning services. 

Later is founded on two success stories that began in 2014: Mavrck, the industry-leading influencer marketing solution (now Later Influence™), and Later, the best social media management platform (now Later Social™) and first-to-market link in bio tool, Later Link in Bio. In 2024, Mavrck and Later officially joined together as one unified business, with a shared vision: to enable the world to make a living with their creativity. 

We’re trusted by the top social platforms, with partnerships and integrations with Meta, TikTok, X/Twitter, LinkedIn, YouTube, and Pinterest. 

We enable marketers to create high-performing content and engage in authentic collaborations with creators to reach new audiences, drive engagement, and generate predictable ROI. 

In Short

• Lead the design and evolution of a scalable data architecture.
• Architect and optimize data pipelines for batch and real-time data processing.
• Implement best practices for distributed data processing.
• Define and enforce data governance policies.
• Ensure data security and compliance with industry regulations.
• Drive innovation in data engineering practices.
• Work closely with cross-functional teams to understand data requirements.
• Develop reusable frameworks and automation tools.
• Guide and mentor data engineers.
• Establish and monitor SLAs for data pipelines.

Requirements

• 10+ years of experience in data engineering or related fields.
• Proven experience leading technical strategy for large-scale data platforms.
• Expertise in cloud technologies (GCP, AWS, Azure).
• Strong proficiency in SQL, Python, and distributed data processing frameworks.
• Experience with streaming data architectures using Kafka or similar technologies.
• Expertise in data modeling and performance tuning for analytical workloads.
• Strong experience designing scalable data pipelines using orchestration tools.
• Ability to lead and influence engineering teams.
• Experience mentoring data engineers.

Benefits

• Competitive salary range based on market data.
• Stock options for permanent team members.
• Eligibility for various benefits plans.
• Inclusive and supportive work environment.
• Opportunities for professional growth and development.