Xebia_ Data Engineer
About Xebia
Xebia is a trusted advisor in the modern era of digital transformation, serving hundreds of leading brands worldwide with end-to-end IT solutions. The company has experts specializing in technology consulting, software engineering, AI, digital products and platforms, data, cloud, intelligent automation, agile transformation, and industry digitization. In addition to providing high-quality digital consulting and state-of-the-art software development, Xebia has a host of standardized solutions that substantially reduce the time-to-market for businesses.
Xebia also offers a diverse portfolio of training courses to help support forward-thinking organizations as they look to upskill and educate their workforce to capitalize on the latest digital capabilities. The company has a strong presence across 16 countries with development centres across the US, Latin America, Western Europe, Poland, the Nordics, the Middle East, and Asia Pacific.
Job Description:
We are looking for a skilled Data science Data Engineer to join our team, working on end-to-end data engineering and data science use cases. The ideal candidate will have strong expertise in Python or Scala, Spark (Databricks), and SQL, building scalable and efficient data pipelines on Azure.
Primary Skills:
Data Engineering & Cloud:
- Proficiency in Azure Data Platform (Data Factory, Databricks).
- Strong skills in SQL and [Python or Scala] for data manipulation.
- Experience with ETL/ELT pipelines and data transformations.
- Familiarity with Big Data technologies (Spark, Delta Lake, Parquet).
ML & MLOps Integration:
- Experience supporting ML pipelines with efficient data workflows.
- Knowledge of MLOps practices (CI/CD, model monitoring, versioning).
Data Optimization & Performance:
- Expertise in data pipeline optimization and performance tuning.
- Experience on feature engineering and model deployment.
Analytical & Problem-Solving:
- Strong troubleshooting and problem-solving skills.
- Experience with data quality checks and validation.
Nice-to-Have Skills:
- Exposure to NLP, time-series forecasting, and anomaly detection.
- Familiarity with data governance frameworks and compliance practices.
- Understanding of retail, or workforce analytics.
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