[Hiring] Staff Data Engineer @Later
Mar 21, 2025 - Later is hiring a remote Staff Data Engineer. đź’¸ Salary: $200,000-228,000 usd. đź“ŤLocation: USA.
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.
Development at Later:
We are builders and innovators on a mission to democratize the creator economy.
At Later, you'll work alongside experts who are redefining what's possible in social commerce, tackling complex challenges from AI-powered content recommendations to systems that process billions of posts daily. While our standards are high and the work is demanding, we believe social media has unprecedented power to create economic opportunity for creators and businesses worldwide.
This isn't just about building software – it's about empowering millions of entrepreneurs, creators, and businesses to transform their digital presence into sustainable growth. We're creating an accessible platform where anyone can thrive in the creator economy, from solopreneurs to global brands.
You'll be challenged to think bigger and move faster than you ever have before. The problems we solve are complex, but for those who embrace the challenge, this will be the most meaningful work of your career. Our vision is ambitious: to empower 1 billion people to make a living through their creativity by putting powerful, intuitive tools in their hands.
If you believe in democratizing digital marketing, enabling authentic connections, and building technology that creates real economic opportunity, Later is where your expertise will make a difference. Let's shape the future of social commerce together.
About this position:
As a Staff Data Engineer at Later, you will be at the forefront of designing and scaling our data platform, integrating multiple data sources, and ensuring high availability, efficiency, and security. You will drive architectural decisions, optimize large-scale data processing, and develop real-time analytics infrastructure. Partnering with cross-functional teams, including data science, product, and engineering, you will play a strategic role in shaping the company's data roadmap, implementing best practices, and influencing long-term data strategies. Your leadership and deep technical expertise will be essential in building a data-driven culture and empowering stakeholders with scalable and reliable data solutions.
What you'll be doing:
- Lead the design and evolution of a scalable data architecture that meets analytical, machine learning, and operational needs.
- Architect and optimize data pipelines for batch and real-time data processing, ensuring efficiency and reliability.
- Implement best practices for distributed data processing, ensuring scalability, performance, and cost-effectiveness of data workflows.
- Define and enforce data governance policies, implement automated validation checks, and establish monitoring frameworks to maintain data integrity.
- Ensure data security and compliance with industry regulations by designing appropriate access controls, encryption mechanisms, and auditing processes.
- Drive innovation in data engineering practices by researching and implementing new technologies, tools, and methodologies.
- Work closely with data scientists, engineers, analysts, and business stakeholders to understand data requirements and deliver impactful solutions.
- Develop reusable frameworks, libraries, and automation tools to improve efficiency, reliability, and maintainability of data infrastructure.
- Guide and mentor data engineers, fostering a high-performing engineering culture through best practices, peer reviews, and knowledge sharing.
- Establish and monitor SLAs for data pipelines, proactively identifying and mitigating risks to ensure high availability and reliability.
We are committed to building an inclusive, supportive place for you to do the best and most rewarding work of your career. If you identify with any of the following, we encourage you to apply!
- 10+ years of experience in data engineering, software engineering, or related fields.
- Proven experience leading the technical strategy and execution of large-scale data platforms.
- Expertise in cloud technologies (Google Cloud Platform, AWS, Azure) with a focus on scalable data solutions (BigQuery, Snowflake, Redshift, etc.).
- Strong proficiency in SQL, Python, and distributed data processing frameworks (Apache Spark, Flink, Beam, etc.).
- Extensive experience with streaming data architectures using Kafka, Flink, Pub/Sub, Kinesis, or similar technologies.
- Expertise in data modeling, schema design, indexing, partitioning, and performance tuning for analytical workloads, including data governance (security, access control, compliance: GDPR, CCPA, SOC 2)
- Strong experience designing and optimizing scalable, fault-tolerant data pipelines using workflow orchestration tools like Airflow, Dagster, or Dataflow.
- Ability to lead and influence engineering teams, drive cross-functional projects, and align stakeholders towards a common data vision.
- Experience mentoring senior and mid-level data engineers to enhance team performance and skill development.
Preferred Qualifications:
- Experience with machine learning infrastructure and integrating ML models into data pipelines.
- Experience with Kappa/Lambda architectures for real-time data processing.
- Background in data observability, lineage tracking, and anomaly detection tools (Monte Carlo, Databand, Great Expectations, etc.).
- Experience working with decentralized data architecture (e.g., Data Mesh principles).
How you work:
- You’re proactive and results-driven, always taking initiative, aligning your actions with company goals, and delivering consistent outcomes.
- Strategic and forward-thinking, you balance immediate needs with long-term opportunities to drive impactful, innovative results.
- Your curiosity fuels success, keeping you sharp on industry trends, competition, and our cross-functional business dynamics.
- Adaptable and resourceful, you handle shifting priorities with ease, manage your time effectively, and know when to ask for support.
- You share insights to help the team stay ahead and make informed decisions.
- You bring positivity and resilience to every challenge, tackling obstacles with grit and optimism that inspires those around you.
- You lead with emotional intelligence, building trust, supporting others, encouraging growth, and fostering strong relationships through empathy and collaboration.
Our approach to compensation:
We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.
Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.
To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted.
Additionally, all permanent team members are granted stock options and are eligible to participate in various benefits plans as part of their overall compensation package.
Salary Range:
$ 200,000- 228,000 USD
*Co-op team members, independent contractors, and freelancers are not eligible for company benefits.
#LI-Remote
Where we work
We have offices in Boston, MA; Vancouver, BC; Chicago, IL; and Vancouver, WA. For select positions, we are open to hiring fully remote candidates. We post our positions in the location(s) where we are open to having the successful candidate be located.
Diversity, inclusion, and accessibility
At Later, we are committed to fostering a culture rooted in an inclusion-first mindset at every level of the company, embracing the importance of hiring and building teams for culture add rather than culture fit. We openly build and maintain unbiased hiring, pay, and promotion practices to create a foundation for an equitable workplace, paving the way for systemic change.
We are committed to creating a diverse environment and are proud to be an equal opportunity employer. All applications will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, national origin, disability, or age. Please let us know if you require any accommodations or support during the recruitment process.
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| đź“Ť | Be aware of the location restriction for this remote position: USA |
| ‼ | Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more. |
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Salary
đź’¸
$200,000-228,000 usd
|
Remote
Location
USA
|
|
Job Type
full-time
|
Posted
Mar 21, 2025
|
| đź“Ť | Be aware of the location restriction for this remote position: USA |
| ‼ | Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more. |
