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
At TripleLift, we believe great work starts with great people. We foster a culture built on collaboration, curiosity, and a shared commitment to making each other better. We move with urgency, challenge convention, and continuously innovate to elevate digital advertising. We value people who bring new perspectives, take ownership, and work together to drive meaningful impact. Learn more about TripleLift and our culture on our LinkedIn Life page.
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TripleLift does not accept unsolicited resumes from recruitment search firms. Any resume submitted without a signed agreement in place will become the property of TripleLift, and no fee will be due.
Skills Required
- Bachelor's degree in Computer Science, a related technical field, or equivalent professional experience
- At least 5 years of professional software engineering experience focused on data and ML processes in production at scale
- Experience optimizing big data and ML pipelines, including Spark and Kafka, at scale
- Fundamental knowledge of ML and AI operations and processes
- Understanding of database technologies such as OpenSearch, Druid, ClickHouse, or InfluxDB
- Proven experience with cross-functional data modeling
- Strong SQL skills
- Expertise in one or familiarity with multiple of Python, Scala, and Java
- Experience with MLflow, Feast, Ray, or other AI training technologies
- Experience with containerization, Kubernetes, and Argo CD
TripleLift Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about TripleLift and has not been reviewed or approved by TripleLift.
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Equity Value & Accessibility — Equity participation and stock option grants are described as meaningful parts of total compensation and are frequently appreciated. Equity is noted alongside bonuses as a valuable upside that contributes to overall satisfaction.
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Leave & Time Off Breadth — Unlimited PTO, paid holidays and sick days, monthly mental health days, and a one‑month sabbatical after five years illustrate a generous time‑off offering. These policies are portrayed as supporting work‑life balance and wellbeing.
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Healthcare Strength — Medical, dental, and vision coverage, life insurance, FSAs, and company‑paid disability insurance are positioned as competitive. Access to wellbeing resources such as Headspace and other programs further bolsters the benefits package.
TripleLift Insights
What We Do
TripleLift is redefining digital advertising by delivering innovative, high-quality ad experiences that create real connections. By combining cutting-edge creative technology, actionable data, advanced targeting, and premium inventory, we empower publishers and brands to discover new opportunities, achieve measurable outcomes, and engage audiences seamlessly across every platform.
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