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Senior Data Engineer - Python, Cloud & Data Warehousing
Job Description
We are seeking a highly skilled and experienced Senior Data Engineer with 10+ years of experience in data engineering or related roles. The ideal candidate will have strong expertise in Python, data warehousing, ETL development, and cloud platforms, with a solid understanding of big data technologies and DevOps practices. This role requires excellent problem-solving abilities, SQL proficiency, and the ability to collaborate effectively in a fast-paced environment.
Key Responsibilities
Design, develop, and maintain scalable data pipelines for ingestion, transformation, and integration of large datasets.
Implement and optimize data models and warehousing solutions across SQL and cloud-native platforms.
Develop efficient ETL workflows using Apache Airflow, NiFi, Informatica, or DataStage.
Leverage Python (Pandas, NumPy, etc.) for data processing, transformation, and automation tasks.
Collaborate with data scientists, analysts, and cross-functional stakeholders to ensure data quality and availability.
Work with cloud platforms (AWS, Azure, or GCP) to architect, deploy, and manage data infrastructure.
Apply best practices in SQL performance tuning, query optimization, and database management.
Incorporate SRE/DevOps practices including CI/CD, containerization (Docker, Kubernetes), and automation.
Monitor, troubleshoot, and enhance system performance and reliability.
Stay updated with emerging technologies in data engineering, big data, and cloud ecosystems.
Required Skills & Experience
10+ years of experience in data engineering or related roles.
Strong proficiency in Python, with hands-on experience using Pandas, NumPy, and other data manipulation libraries.
Solid experience in data warehousing concepts, data modeling, and database technologies (SQL Server, PostgreSQL, MySQL, Snowflake, BigQuery, Redshift).
Expertise in ETL tools and techniques (Airflow, NiFi, Informatica, DataStage).
Hands-on experience with cloud platforms: AWS, Azure, or GCP.
Familiarity with big data technologies: Hadoop, Spark, Kafka (preferred).
Advanced SQL expertise, including writing and optimizing complex queries.
Knowledge of data science fundamentals such as machine learning basics and statistical analysis.
Understanding of DevOps tools & practices: CI/CD, Docker, Kubernetes.
Strong problem-solving, analytical, and communication skills.
Wünschenswerte Fähigkeiten
- MySQL
- Numpy
- Pandas
- PostgreSQL
- Python
- Redshift
- SQL
- SQL Server
Berufserfahrung
- Data Engineer
Sprachkenntnisse
- English
Hinweis für Nutzer
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