Data Engineer

Job Title: Data Engineer

Job Description:

Seeking a skilled Data Engineer with a robust background in PySpark and extensive experience with AWS services, including Athena and EMR. The ideal candidate will be responsible for designing, developing, and optimizing large-scale data processing systems, ensuring efficient and reliable data flow and transformation.

Key Responsibilities:

• Data Pipeline Development: Design, develop, and maintain scalable data pipelines using PySpark to process and transform large datasets.

• AWS Integration: Utilize AWS services, including Athena and EMR, to manage and optimize data workflows and storage solutions.

• Data Management: Implement data quality, data governance, and data security best practices to ensure the integrity and confidentiality of data.

• Performance Optimization: Optimize and troubleshoot data processing workflows for performance, reliability, and scalability.

• Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.

• Documentation: Create and maintain comprehensive documentation of data pipelines, ETL processes, and data architecture.

Required Skills and Qualifications:

• Education: Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.

• Experience: 5+ years of experience as a Data Engineer or in a similar role, with a strong emphasis on PySpark.

• Technical Expertise:

o Proficient in PySpark for data processing and transformation.

o Extensive experience with AWS services, specifically Athena and EMR.

o Strong knowledge of SQL and database technologies.

o Experience with Apache Airflow is a plus

o Familiarity with other AWS services such as S3, Lambda, and Redshift.

• Programming: Proficiency in Python; experience with other programming languages is a plus.

• Problem-Solving: Excellent analytical and problem-solving skills with attention to detail.

• Communication: Strong verbal and written communication skills to effectively collaborate with team members and stakeholders.

• Agility: Ability to work in a fast-paced, dynamic environment and adapt to changing priorities.

Preferred Qualifications:

• Experience with data warehousing solutions and BI tools.

• Knowledge of other big data technologies such as Hadoop, Hive, and Kafka.

• Understanding of data modeling, ETL processes, and data warehousing concepts.

• Experience with DevOps practices and tools for CI/CD.