Data Engineer, Databricks, PySpark

Job not on LinkedIn

🕒 August 24

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 23%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Avanda Group

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2020

🤝 B2B

🎯 Recruiter

🏢 Enterprise

B2B • Recruitment • Enterprise

Avanda Group is a Swiss-based professional services consultancy and digital workforce solutions provider that delivers IT and digital transformation services across Switzerland and Europe. The firm supplies client-embedded consultants, dedicated and nearshore teams, managed services, executive search, and compliant payroll/MSP solutions to help enterprise clients scale technology teams, recruit leadership, and manage external workforce operations. Avanda focuses on data, business applications, security, and digital transformation, combining delivery leadership with talent sourcing and operational compliance.

📋 Description

• Understand data-related dependencies, processes, system interactions, and source-of-truth concepts • Identify and trace data flows across multiple source and target systems • Investigate issues across system interfaces, data pipelines, and downstream processes to determine root cause • Use Databricks and SQL for data analysis, assumption validation, inconsistency detection, and incident resolution • Maintain and improve reliable data pipelines through validation, reconciliation, monitoring, and documentation • Work within established version-control, deployment, change, and release procedures • Collaborate in an agile delivery environment, owning tasks end-to-end • Support critical data engineering activities and ensure continuity and knowledge transfer

🎯 Requirements

• Proven experience designing, developing, testing, and operating production-grade ETL/ELT pipelines • Hands-on experience with Databricks, Python/PySpark, and SQL • Experience integrating and reconciling data across enterprise systems (REST APIs, ITSM, ITFM, CMDB, IAM, ERP, monitoring, or similar) • Experience with data validation, quality checks, reconciliation, monitoring, lineage, and schema evolution • Git-based version control, code reviews, automated testing, CI/CD or comparable practices • Experience with DEV/TEST/PROD environments and structured release/change processes • Strong root-cause analysis skills across interfaces, pipelines, and downstream systems • Fluent English

🏖️ Benefits

• Full remote work arrangement