> Markdown version of [/jobs/ext/4174721-senior-data-engineer-remote-telecommute](https://www.wearedevelopers.com/jobs/ext/4174721-senior-data-engineer-remote-telecommute). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - Remote / Telecommute - **Company:** CYNET SYSTEMS INC. - **Location:** Hartford, CT, United States (Remote available) - **Experience:** Expert - **Salary:** $124,800.0 - $135,200.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Application Integration Architecture, Microsoft Azure, Cloud Computing, Data Integration, Python (Programming Language), Data Mesh, Data Streaming, Multi-Cloud, Pyspark, Apache Kafka, Data Pipelines, Api Management, Databricks - **Published:** October 30, 2026 - **Apply:** https://www.careerjet.com/jobad/us34e68fa935d40fc448b0717fdb386090 ## About the Role * 8+ years of overall IT experience with 6 years as a Data Engineer. * Experience in providing data engineering solutions. * Working knowledge of cloud platforms (Azure/AWS). * Working knowledge of Databricks, Data Mesh, and Data as a Product. * Working knowledge of Python. * Working knowledge of data streaming tools (Kafka, EventHub, Kinesis, SNS). * Cloud-based API management experience is nice to have. * Immuta experience is nice to have. * Multi-cloud and on-prem application integration experience is nice to have. ## Description The candidate will review and translate requirements to end-to-end technical design with a goal of building data products. The candidate will develop pipelines in Databricks using PySpark and DBT to onboard various sources. The role requires working knowledge in Kafka to stream data into the Databricks platform. The successful candidate will identify common approaches and best practices to data integration such as metadata-driven ingestion, data validations, and complex data type handling. The candidate will drive standards for reusability while developing pipelines, create or update documentation associated with key decisions on requirements, design, and development, and liaise with architects, data owners, and users for daily reviews to ensure high quality of deliverables.