Senior Data Engineer

Position:

Location:

Experience:

Job Summary:

We are seeking an experienced Senior Data Engineer with a strong background in PySpark, Spark, and Big Data technologies. The ideal candidate will have over five years of hands-on experience designing, building, and optimizing large-scale data processing systems and pipelines.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL processes using PySpark and Spark.
• Perform data wrangling, transformation, and integration across diverse data sources.
• Optimize the performance and reliability of data processing workflows.
• Implement data quality frameworks to ensure data accuracy and integrity.
• Develop and maintain data architectures and data models to support business needs.
• Collaborate with cross-functional teams including data analysts, software engineers, and business stakeholders to understand data requirements.
• Stay updated with the latest advancements in Big Data tools, frameworks, and best practices.
• Mentor and guide junior data engineers in technical and professional growth.

Required Skills and Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in data engineering roles.
• Expertise in PySpark and Spark for large-scale data processing.
• Strong understanding of Big Data ecosystems and technologies (e.g., Hadoop, Hive).
• Hands-on experience with ETL development, data modeling, and data warehousing.
• Proficiency in programming languages such as Python, Scala, or Java.
• Experience with cloud platforms like AWS, Azure, or Google Cloud.
• Strong problem-solving skills and a detail-oriented mindset.
• Excellent communication and collaboration skills.

Preferred Qualifications:

• Experience with containerization and orchestration tools like Docker and Kubernetes.
• Knowledge of SQL and relational database management systems.
• Familiarity with data orchestration tools like Airflow, Prefect, or similar.