Why this grade
This listing scored 54/100, which is a D. It lost the most ground on pay transparency.
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 15 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Role specificity 6 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
This listing does not state a salary
$125k – $160k
That is the middle half of what comparable roles paid on this board over the last 90 days — 37 listings that did publish a figure, median $140k. It is not this employer's offer, and we have no idea what they pay. It is only what the rest of the market advertised.
Data Science Developer Senior Full Time
Job Description
- Architect, administer, and optimize Databricks workspaces, clusters, jobs, and workflows.
- Design and develop scalable Azure-based data engineering solutions, including Data Lake, Data Factory, Synapse, Key Vault, etc.
- Build high-performance data pipelines using Python and PySpark.
- Work with Hadoop-based platforms and distributed storage systems.
- Implement and manage real-time data streaming solutions and ingestion pipelines.
- Ensure proper configuration, monitoring, governance, and performance tuning of data platforms.
- Integrate CI/CD pipelines on Azure and work with containerization technologies (Docker/K8s).
- Develop and optimize SQL queries, stored procedures, and data models using MS SQL.
- Collaborate with architects, data scientists, and engineering teams to deliver enterprise-grade solutions.
- Define best practices, coding standards, and data engineering frameworks across the organization.
- Troubleshoot complex data issues and ensure high availability of mission-critical data systems.
Requirements
- Minimum 10+ years of total IT experience.
- Minimum 6+ years strong experience in the following areas: Databricks Administration , Azure Cloud , Python & PySpark , Hadoop ecosystem , Data streaming & data pipeline engineering , MS SQL
- Proven experience architecting large-scale distributed data systems.
- Strong understanding of data lakes, data warehousing, and big data architecture patterns.
Nice-to-Have Skills
- Experience with Apache Spark optimization and tuning.
- Hands-on experience with CI/CD pipelines on Azure (GitHub Actions, Azure DevOps, etc.).
- Knowledge of containers (Docker, Kubernetes).
- Understanding of MLOps or advanced analytics integrations.
Originally posted on Himalayas
Apply for this role Opens himalayas.app — the link as listed; we have not yet verified it is the employer's own page
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Where this listing came from
- 04 Oct 2026 Himalayas first sighting
Seen on 1 board over 0 days.