Browse remote Spark opportunities and confirm accepted candidate locations before applying.
This page focuses on remote roles with visible candidate-location eligibility for developers, engineers, DevOps, data, QA, support, and other IT professionals.
Use Spark as a stack filter without changing the original role titles, comparing seniority, accepted countries, and application readiness before opening the full role page.
Lead the design and implementation of complex data ingestion pipelines using PySpark, Databricks Intelligence Platform, and AWS services (S3, IAM roles and policies), including Kafka/streaming architectures, schema evolution
Top Us Wealth Management Firm · Engineering
Design and implement Python Data Engineering solutions
Reality Defender · Data Science
Design, build, and operate large-scale data processing pipelines handling multi-terabyte and streaming datasets, including audio/video transcoding, feature extraction, and preprocessing workflows.
Parsons Corporation · Data Science
Design, develop, and maintain scalable data pipelines and ETL processes to ingest, transform, and enrich large volumes of chemical and biological threat data from diverse sources.
SumerSports LLC · Data Science
Build and operate robust data pipelines for ingestion, cleaning, and transformation using Databricks, Airflow, or Dagster.
Teravision Technologies · Data Science
Fully remote position.
Penn Foster · Data Science
Developing Python, SQL, and PySpark based applications and data flows in Databricks
Innovatus Technology Consulting · Data Science
Design, develop, and maintain scalable data pipelines to ingest, transform, and curate logistics, maintenance, and supply chain data from multiple USMC systems.
Cotiviti · Data Science
Create, maintain and execute intermediate to advanced Spark scripts for data management and data validation, and data integration.
Dorle Controls LLC · Data Science
, and designing scalable data lake and data warehouse solutions. Experience across multiple data platforms (Databricks, Snowflake, Azure Data Factory, Synapse, etc.) is a strong advantage. Key Responsibilities 1.
Nebius · Data Science
Design, develop, and maintain scalable data pipelines.
Shift5 · Data Science
Design & Build Pipelines: Design, build, and maintain robust, scalable batch and streaming data processing, storage, and integration pipelines.
ShyftLabs · Data Science
Design, build, and maintain scalable and reliable batch and real-time ETL/ELT data pipelines using cloud services such as GCP Dataflow, Cloud Functions, Pub/Sub, and Cloud Composer.
Anteriad · Data Science
Partner with technical and non-technical stakeholders to translate business requirements into scalable, reliable, and maintainable data engineering solutions.
Cutsforth, LLC · Data Science
Regularly design, develop, and maintain data pipelines that support operational, analytical, and machine learning workloads
OneSix · Data Science
Data Engineering & DevelopmentDevelop and maintain robust data integration pipelines (ETL and ELT) to process large volumes of financial data across cloud and on-premise environments.
Baseten · G&A
Design and maintain core data models and semantic layers
Samsara · Revenue Operations
You want to impact the industries that run our world: Your efforts will result in real-world impact—helping to keep the lights on, get food into grocery stores, reduce emissions, and most importantly
XKTalent Inc. - Rimutee · Data Science
📌 What You'll Bring ✅ 5+ years of experience in designing and building scalable data lakes in cloud environments. ✅ Advanced programming skills in Python or Java.
Koantek · Data Science
Guide Big Data Transformations:Implementation of comprehensive big data projects, including the development and deployment of innovative big data and AI applications.
Valtech · Data Science
A curious problem solver who challenges the status quo
Rackner · Data Science
Build and maintain end-to-end Ingest → Transform → Expose pipelines using Airflow, Spark, dbt, and Iceberg.
Astrana Health · Data Science
Put Patients First
Collectiv · Data Science
Design and implement modern data platforms leveraging Microsoft Fabric (OneLake, Lakehouse, Data Factory, Power BI) and Databricks (Spark, Delta Lake, SQL Warehouses)
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