Senior Data Engineer
Toronto, Ontario, Canada
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingCreate and maintain optimal data pipeline architecture
Assemble large, complex data sets that meet business requirements
Automate manual processes and redesign infrastructure for scalability
Build data extraction and loading infrastructure using Spark, EMR, Kafka
Support product, engineering and analytics teams with data technical issues
From the employer’s posting
Create and maintain optimal data pipeline architecture
Explore and assemble large, complex data sets that meet functional / non-functional business requirements.
automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability
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
Education & alternatives
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.
Tools in this posting
- Java
- Python
- Scala
- SQL
- ClickHouse
- Kafka
- MLflow
- Spark
Source — Tool mentions in context
- 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
- 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
- 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.
- 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
- 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
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 23, 2026 · 36 days ago
- Recorded sightings
- 20
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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
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.
Please review our Privacy Policy for information about how TripleLift handles personal information.
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.
Source details
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- Pay
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- Location & working pattern
Toronto, Ontario, Canada
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