Senior Level Pipeline Engineer Jobs
Senior level pipeline engineer jobs put experienced engineers in charge of system design, project ownership, and the technical teams executing complex infrastructure. Openings concentrate in Consulting & Professional Services and Technology & Software, with 83% remote or hybrid availability, and employers like Kennedy/Jenks Consultants and 42dot hiring at this level now.
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Showing 5 of 6+ Senior Level Pipeline Engineer jobs
INTRODUCTION
We are looking for the best
About us
42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles. We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system. Our AI Data Pipeline Engineers build up the core data processing pipelines and datasets readiness for autonomous driving cutting edge algorithms. We develop the distributed system of a scalable data pipeline for large-scale dataset (millions of scenes), as well as high-performance data serving SDKs for ML model training / evaluation. The data pipelines we deliver could highly improve the efficiency of ML model development lifecycle, including training, evaluation, deployment, as well as monitoring in the cloud environment.
Responsibilities
- Develop high scale, reliable data extraction pipeline to extract millions of raw data from data collection fleet and convert to high-value scene data
- Develop data labeling pipelines to perform the auto labeling inferences for autonomous driving algorithms
- Develop advanced autonomous driving data SDK, including scene data search, datasets preparation, dataset loading, etc.
- Build up the data lakehouse for autonomous driving scene dataset, including the sensor data, calibration data, as well as annotation data
- Dig into performance bottlenecks all along the data processing pipelines, from data processing latency, data search latency to Test Procedure (TP) coverage
- Bootstrap and maintain infrastructure for data platform components—data processing pipeline, database, data lakehouse and data serving
- Collaborate with cross-functional teams, including ML algorithm, ML application, and Cloud Infra to align data pipelines with overall autonomous driving system architecture
QUALIFICATIONS
- Bachelor's degree or higher in Computer Science, Engineering, Robotics, or a similar technical field
- Minimum of 7 years of experience in Data Engineering, DataOps or ML Platform roles
- Proficient in Python and solid experience in Python SDK development
- Solid hands-on experience with data pipeline job orchestration with Databricks Workflows or Apache Airflow, as well as integrating data pipelines with machine learning models
- Solid working experience in Databases (e.g., MongoDB, PostgreSQL, etc)
- Extensive experience with data technologies and architectures such as Data Warehouse (e.g., Hive) or Lakehouse (e.g., Delta Lake)
- Experience with Apache Spark or other big data computing engines
- Excellent leadership and communication skills, with a demonstrated ability to lead technical projects
PREFERRED QUALIFICATIONS
- Experience with autonomous vehicle sensor data (e.g., LiDAR, camera, radar)
- Experience with ML model training lifecycle (e.g., data preparation, model training / validation / deployment, etc)
- Understanding of modern AI frameworks (e.g., PyTorch, TensorFlow etc.)
- Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data
INTRODUCTION
We are looking for the best
About us
42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles. We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system. Our AI Data Pipeline Engineers build up the core data processing pipelines and datasets readiness for autonomous driving cutting edge algorithms. We develop the distributed system of a scalable data pipeline for large-scale dataset (millions of scenes), as well as high-performance data serving SDKs for ML model training / evaluation. The data pipelines we deliver could highly improve the efficiency of ML model development lifecycle, including training, evaluation, deployment, as well as monitoring in the cloud environment.
Responsibilities
- Develop high scale, reliable data extraction pipeline to extract millions of raw data from data collection fleet and convert to high-value scene data
- Develop data labeling pipelines to perform the auto labeling inferences for autonomous driving algorithms
- Develop advanced autonomous driving data SDK, including scene data search, datasets preparation, dataset loading, etc.
- Build up the data lakehouse for autonomous driving scene dataset, including the sensor data, calibration data, as well as annotation data
- Dig into performance bottlenecks all along the data processing pipelines, from data processing latency, data search latency to Test Procedure (TP) coverage
- Bootstrap and maintain infrastructure for data platform components—data processing pipeline, database, data lakehouse and data serving
- Collaborate with cross-functional teams, including ML algorithm, ML application, and Cloud Infra to align data pipelines with overall autonomous driving system architecture
QUALIFICATIONS
- Bachelor's degree or higher in Computer Science, Engineering, Robotics, or a similar technical field
- Minimum of 7 years of experience in Data Engineering, DataOps or ML Platform roles
- Proficient in Python and solid experience in Python SDK development
- Solid hands-on experience with data pipeline job orchestration with Databricks Workflows or Apache Airflow, as well as integrating data pipelines with machine learning models
- Solid working experience in Databases (e.g., MongoDB, PostgreSQL, etc)
- Extensive experience with data technologies and architectures such as Data Warehouse (e.g., Hive) or Lakehouse (e.g., Delta Lake)
- Experience with Apache Spark or other big data computing engines
- Excellent leadership and communication skills, with a demonstrated ability to lead technical projects
PREFERRED QUALIFICATIONS
- Experience with autonomous vehicle sensor data (e.g., LiDAR, camera, radar)
- Experience with ML model training lifecycle (e.g., data preparation, model training / validation / deployment, etc)
- Understanding of modern AI frameworks (e.g., PyTorch, TensorFlow etc.)
- Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data
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Find JobsSenior Level Pipeline Engineer Job Market
Who's Hiring
Top Industries Hiring
- Consulting & Professional Services
- Technology & Software
Senior Level Pipeline Engineer Jobs: Frequently Asked Questions
How do I get a senior level pipeline engineer job?
Senior level pipeline engineer roles go to candidates who can demonstrate ownership of large-scale projects from design through commissioning. Employers at this level look for deep expertise in pipeline integrity, hydraulics, or facilities engineering, plus a record of leading cross-functional teams and making high-stakes technical decisions independently. Highlighting projects where you set the technical direction, not just executed it, gives your application the strongest edge.
Which companies hire senior level pipeline engineers?
Companies hiring senior level pipeline engineers right now include Kennedy/Jenks Consultants and 42dot, based on current listings on Migrate Mate as of November 2026. At this level, hiring comes primarily from major oil and gas operators, midstream infrastructure firms, and large engineering and construction contractors managing complex capital projects.
Are there remote senior level pipeline engineer jobs?
Yes, though most roles still require on-site or field presence given the hands-on nature of pipeline work. About 83% of senior level pipeline engineer openings are remote or hybrid as of November 2026, with hybrid arrangements most common in design, project management, and regulatory compliance functions rather than operations or inspection roles.
What makes a pipeline engineer role senior level?
Senior level pipeline engineer roles carry a fundamentally different scope than mid-level positions. Engineers at this stage own full project lifecycles, serve as the technical authority on design decisions, and are accountable for safety, regulatory compliance, and cost outcomes. They also mentor junior and mid-level engineers, interface directly with clients or executive stakeholders, and are expected to resolve complex problems with limited supervision.
Which industries hire the most senior level pipeline engineers?
Senior Level pipeline engineer roles concentrate in Consulting & Professional Services and Technology & Software, based on current listings on Migrate Mate as of November 2026. These sectors drive demand because they operate or expand large-scale transmission, gathering, and distribution systems that require experienced engineers to manage integrity, permitting, and capital project execution at the highest technical level.