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Data Engineer
2 months ago
Koniclab is a leading innovator in the energy sector, leveraging advanced algorithms and artificial intelligence to optimize energy storage and maximize its value. Our mission is to empower customers to participate effectively in multiple energy markets, enhancing the efficiency and profitability of renewable energy resources.
Job Role and ResponsibilitiesAs a ML Ops / Data Engineer at Koniclab, you will play a critical role in supporting our data engineering infrastructure. Your responsibilities will include:
- Design and Development: Contribute to the design, development, and implementation of our data engineering tools, workflows, processes, and platforms. Enhance the architectural foundations and integrate new data management technologies to ensure seamless data flow.
- Code Quality and Mentorship: Develop clean, maintainable, and well-documented code that adheres to best practices. Mentor and support team members in the continued improvement of coding practices within the Data Science team.
- Data Quality Management: Continuously enhance data quality across multiple dimensions, ensuring accuracy, availability, performance, and accessibility. Provide a clear understanding of data within the company.
- Technical Support: Provide backup and escalation support to the tech-on-call team, ensuring seamless technical operations.
- Communication: Communicate effectively across Software and Data Science teams, fostering collaboration and knowledge sharing.
To succeed in this role, you will need:
- 5+ years of Python experience
- 3+ years of working in technical teams, building data pipelines, delivering productionized code, building/maintaining live applications, developing tooling, and improving backtesting frameworks
- 2+ years of orchestrating machine learning workflows
- Proficiency with Orchestration and IaC in AWS (e.g., Terraform, Kubernetes, RabbitMQ, Airflow), Git, containerization (Docker), database management (e.g., Postgres, Alembic)
- Fluent in Python and its wider numerical ecosystem (e.g., Pandas, NumPy, Polars, Pydantic)
The following skills are highly desirable but not essential:
- Relational database design
- Cloud infrastructure experience
- Experience with monitoring frameworks (e.g., Prometheus)
- Experience archiving data to Parquet on S3 and creating tools for API/Grafana queries
- Experience centralizing diverse datasets for analytics, visualization, and machine learning
- Familiarity with time-series forecasting and/or optimization
- Experience with data visualization and dashboards (e.g., Grafana, Superset)
- Familiarity with machine learning and associated techniques (feature engineering, boosting methods, LightGBM)
Koniclab values diversity and offers a highly supportive, challenging, and focused environment for delivering high-quality work. You will receive a competitive salary, flexible working arrangements, and opportunities for personal development.
