We’re seeking a Senior Data Engineer to help design, build, and maintain the data infrastructure that powers our AI capabilities. You’ll work closely with our engineering and product teams to ensure our data systems are reliable, scalable, and optimized for growth. This role is ideal for someone who thrives in early-stage environments and enjoys solving complex data challenges.
What You’ll Do:
- Design, build, and maintain scalable, secure, and high-performance data pipelines that support AI-driven content generation, marketing analytics, and customer engagement (among other use cases).
- Design and develop APIs (e.g., using FastAPI) to expose data from relational, graph, vector databases and cloud storage objects for real-time applications.
- Enable low-latency inference, feature retrieval for downstream systems.
- Build and maintain backend services that orchestrate ELT/ETL workflows, trigger pipelines, and manage data processing jobs and serve real-time data.
- Integrate with orchestration tools like Prefect and cloud services on AWS.
- Develop ETL/ELT processes to integrate structured and unstructured data from multiple sources, including CRM systems, internal databases, and external APIs.
- Optimize data workflows to support real-time insights and AI model performance.
- Develop and maintain data-driven decision-support systems that help clients optimize content strategy and customer engagement.
- Deploy, manage and optimize cloud-based data infrastructure (preferably AWS) to support large-scale AI applications and high-throughput processing.
- Optimize data storage, indexing, retrieval, and processing performance to enhance AI-driven marketing workflows and automation systems.
- Implement best practices for data security, governance, access control and compliance across all data operations.
- Work closely with AI specialists, software engineers, and product managers to align data architecture with business needs and AI-driven use cases.
- Define and enforce data governance policies and best practices for handling customer data, content assets, and campaign analytics pipelines.
- Support AI model training, fine-tuning and deployment by structuring and optimizing datasets and embeddings.
Requirements:
- 5+ years of experience in data engineering, data science, or AI/ML data infrastructure.
- Strong programming skills in Python, SQL, and distributed computing frameworks.
- Hands-on experience building ETL/ELT pipelines and real-time data streaming (Kafka, Apache Airflow, Prefect, or similar tools).
- Proficiency in cloud platforms (AWS preferred, GCP, or Azure), including serverless data processing and large-scale data storage, and orchestration.
- Strong knowledge of database management (SQL, NoSQL, vector databases).
- Experience building data crawlers, connectors, or pipelines that ingest large volume of external data sources into workflows.
- Experience working with vector databases or orchestrating RAG (Retrieval-Augmented Generation) pipelines.
- Strong communication skills and the ability to work cross-functionally with technical and non-technical teams.
- Familiarity with enterprise data security, governance, compliance, and encryption best practices.
- Strong written and spoken English — all technical documentation and client reviews are in English
Nice-to-Have:
- Experience working with AI-driven applications, NLP workflows, and machine learning pipelines
Client and Domain:
- Client: a software company
- Country: Canada
- Domain: AI/Data platform
