Remote Spark Jobs

What’s on this page

Every remote role on 101 Careers that mentions Spark — data engineers building large-scale transformation pipelines, PySpark and Scala Spark specialists tuning jobs that process terabytes, ML engineers training on distributed clusters, and the platform teams who keep the clusters alive. Spark earned its dominance by solving the problem its predecessor left behind: it moved big-data processing into memory, and suddenly the iterative work — machine learning, interactive queries, streaming — that MapReduce made painfully slow became practical. Two decades of ecosystem drift later it remains the default engine for large-scale data transformation, and the lakehouse platforms the industry standardized on run Spark jobs under the hood, which keeps demand steady even as the marketing terms shift. The work suits distributed teams naturally: clusters were always remote machines, notebooks are shared URLs, and the artifacts are git-tracked pipelines rather than whiteboards. The pool matches the skill in title or description rather than trusting job titles, because "data engineer" and "data platform engineer" listings routinely list Spark in the requirements without putting it in the title. The 107 roles below are sorted newest first and re-checked every few hours so nothing here is a dead link. 10 publish a salary range — data-engineering skills are among the strongest we track. Apply direct, no account needed. Natural companions: our Databricks and Kafka hubs cover the platforms most Spark pipelines live beside.

Companies hiring right now

BCD Travel, Chainguard, Parkinson Canada, Bright Vision Technologies, Lokal, Integrate, Cosuno, Shield AI and others are currently listing here.

How often this updates

Employer ATS boards are re-read every six hours and partner feeds every three. Roles that disappear from their source are retired automatically, so nothing on this page should be a dead link. Prefer it as a feed? RSS and a free JSON API are both open.