Senior Data Engineer
New
L
LimeShared Micromobility
This is a remote position with a requirement for candidates to reside in Canada to maintain effective collaboration across teams.Full-TimeSenior
SalaryCA$136K - CA$187K
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Job Details
- Experience
- 5+ years of relevant industry experience in data engineering, distributed systems, or a related field.
- Required Skills
- AWSPythonSQLKafkaSnowflakeAirflowSparkdbt
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field, or equivalent practical experience.
- 5+ years of relevant industry experience in data engineering, distributed systems, or a related field.
- Track record of independently delivering and operating significant production data products end to end.
- Experience using AI-assisted development tools to support coding, debugging, and testing.
- Deep experience building and scaling cloud-based data platforms, preferably using AWS and Snowflake.
- Expertise in developing, optimizing, and debugging complex data transformations using Python and high-performance SQL.
- Strong understanding of data modeling, ETL/ELT architecture, schema design, and transformation frameworks such as dbt.
- Experience designing reliable workflows using orchestration tools such as Airflow.
- Hands-on experience with distributed processing or streaming technologies such as Spark, Flink, or Kafka.
- Experience establishing or improving data quality, testing, observability, lineage, and operational practices.
- Ability to participate in a shared on-call rotation including occasional after-hours, weekend, and holiday coverage.
Responsibilities
- Own the end-to-end design, delivery, and operation of major data products, including high-throughput ETL/ELT pipelines, transformation workflows, and storage solutions.
- Partner with engineering, product, and business stakeholders to define requirements and drive projects from design through production.
- Develop performance-tuned transformations and services using Python, SQL, and dbt.
- Author technical designs and RFCs communicating architecture, risks, and operational considerations.
- Lead projects improving engineering excellence, such as data observability, lineage, incident response, and deployment safety.
- Design and operate scalable batch and real-time data solutions using technologies such as Spark, Flink, and Kafka.
- Partner with the ML Platform team to deliver datasets for model training and inference.
- Participate in the team's on-call rotation, responding to incidents, troubleshooting issues, and contributing to root cause analysis.
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