The job, in the employer's words
About TripleLift
We're TripleLift, an advertising platform on a mission to elevate digital advertising through beautiful creative, quality publishers, actionable data and smart targeting. Through over 1 trillion monthly ad transactions, we help publishers and platforms monetize their businesses. Our technology is where the world's leading brands find audiences across online video, connected television, display and native ads. Brand and enterprise customers choose us because of our innovative solutions, premium formats, and supportive experts dedicated to maximizing their performance.
As part of the Vista Equity Partners portfolio, we are NMSDC certified, qualify for diverse spending goals and are committed to economic inclusion. Find out how TripleLift raises up the programmatic ecosystem at triplelift.com.
Overview
TripleLift is seeking a Senior Data Engineer to join a small, influential Data Engineering team. This hire will be responsible for expanding and optimizing our data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Senior Data Engineer will support our software engineers, product managers, business intelligence analysts and data scientists on data initiatives, and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
Responsibilities
- Create and maintain optimal data pipeline architecture,
- Explore and assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Spark, EMR, Kafka and other big data technologies
- Work with stakeholders across different teams, including product managers, engineers and analysts to assist with data-related technical issues and support their data infrastructure needs.
Education & Requirements
- Bachelor’s degree in Computer Science, a related technical field, or equivalent professional experience.
- Minimum of 5 years of professional software engineering experience, with a strong focus on data and ML processes running in production at scale.
- Experience with optimizing big data and ML pipelines like Spark and Kafka at scale
- Fundamental knowledge of ML and AI operations and processes. Experience in MLFlow, Feast, Ray, and other AI training technologies a plus
- Understanding of a variety of database technologies such as OpenSearch, Druid, Clickhouse, InfluxDB, etc
- Proven track record of cross-functional data modeling
- Strong command of SQL and expertise in one or familiarity with multiple of the following languages: Python, Scala, Java
- Experience in containerization, K8s and ArgoCD is a plus
- Medical, Dental & Vision Plans
- Flexible PTO
- 401k w/ employer match
*Full-time employees are eligible for comprehensive benefits (subject to the terms of applicable plans/policies/agreements, which will be made available to you after commencing employment).
Life at TripleLift
At TripleLift, we’re a team of great people who like who they work with and want to make everyone around them better. This means being positive, collaborative, and compassionate. We hustle harder than the competition and are continuously innovating.
Learn more about TripleLift and our culture by visiting our LinkedIn Life page.
Establishing People, Culture and Community Initiatives
At TripleLift, we are committed to building a culture where people feel connected, supported, and empowered to do their best work. We invest in our people and foster a workplace that encourages curiosity, celebrates shared values, and promotes meaningful connections across teams and communities. We want to ensure the best talent of every background, viewpoint, and experience has an opportunity to be hired, belong, and develop at TripleLift. Through our People, Culture, and Community initiatives, we aim to create an environment where everyone can thrive and feel a true sense of belonging.
Privacy Policy
Please see our Privacy Policies on our TripleLift and 1plusX websites.
TripleLift does not accept unsolicited resumes from any type of recruitment search firm. Any resume submitted in the absence of a signed agreement will become the property of TripleLift and no fee shall be due.
Benefits mentioned
- Medical, Dental & Vision Plans
- Flexible PTO
- 401k w/ employer match
- *Full-time employees are eligible for comprehensive benefits (subject to the terms of applicable plans/policies/agreements, which will be made available to you after commencing employment).
- Salary range transparency
- $130,000—$160,000 USD
Requirements mentioned
- Bachelor’s degree in Computer Science, a related technical field, or equivalent professional experience.
- Minimum of 5 years of professional software engineering experience, with a strong focus on data and ML processes running in production at scale.
- Experience with optimizing big data and ML pipelines like Spark and Kafka at scale
- Fundamental knowledge of ML and AI operations and processes. Experience in MLFlow, Feast, Ray, and other AI training technologies a plus
- Understanding of a variety of database technologies such as OpenSearch, Druid, Clickhouse, InfluxDB, etc
- Proven track record of cross-functional data modeling
- Strong command of SQL and expertise in one or familiarity with multiple of the following languages: Python, Scala, Java
- Experience in containerization, K8s and ArgoCD is a plus
No Mondays shows this listing as the employer published it. Check the details on the employer's site before you apply.