Note: The job is a remote job and is open to candidates in USA. Voltus is seeking a Senior Data Infrastructure Engineer to join our growing team. This role will put you at the center of a strategic initiative to strengthen our core data infrastructure, empowering analysts and enabling consistent reporting as Voltus grows.

Responsibilities

• Own and maintain our data pipeline architectures (e.g., critical data ingestion services, ETL pipelines, database mirroring and warehousing), ensuring they are reliable, monitored, and meet SLAs
• Manage and evolve our data modeling environments and provide a smooth, well-documented workflow for analysts and engineers
• Operate and improve our orchestration systems (Dagster), ensuring jobs run reliably and are observable
• Evaluate and rationalize data tooling from Databricks and notebooks (Marimo, Jupyter) to BI/analytics platforms (Redash and alternatives) and guide Voltus toward a sustainable, coherent data platform
• Implement observability for data systems (logging, alerting, metrics) so issues are detected early and data quality is continuously monitored
• Champion data governance and documentation, making datasets well-defined, trustworthy, and easy to navigate
• Collaborate with analysts, data scientists, and platform engineers to ensure the infrastructure you build is intuitive, scalable, and solves real-world problems
• Lay the groundwork for advanced applications by making Voltus’ data reliably accessible via well-documented interfaces, positioning us to adapt to future ML and AI use cases

Skills

• Proven experience in a data engineering or infrastructure role, with responsibility for production-grade pipelines and data systems
• Skilled in a programming language such as Python (Bonus Go)
• Deep experience with ETL/ELT pipelines, dbt, and integrating disparate data sources into warehouses/lakes
• Familiarity with cloud data platforms (AWS, GCP) and modern data tooling. We are running on AWS
• Experienced in workflow orchestration (Airflow, Dagster, or similar)
• Comfortable evaluating tradeoffs across notebook and analysis platforms (Jupyter, Marimo, Databricks) and recommending sustainable solutions
• Knowledge of BI/analytics tools (Redash, Looker, Mode, Superset, etc.) and how to support or migrate to them
• Strong understanding of data quality, governance, and observability
• A clear communicator who can work across technical and non-technical teams to define requirements and deliver solutions
• Comfortable taking ownership end-to-end of critical data infrastructure and serving as a point person for reliability and direction
• Familiarity with observability/monitoring tools (e.g., Datadog, Prometheus)
• Experience and Familiarity with Delta Lake, Databrick, Duckdb
• Exposure with LLM-based applications and toolchains (LangChain, LlamaIndex, lite-llm)
• Experience with vector databases (Pinecone, Qdrant, Chroma)

Benefits

• Full-Time employment type
• Remote workplace type
• Work primarily from their home country with approval required for travel to other countries
• Equal employment opportunity regardless of gender identity, race, nationality, religion, age, sexual orientation, veteran status, disability status, or marital status

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