Data Engineer
Role details
Job location
Tech stack
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., * Data Pipeline Development: Design, develop, and maintain scalable data pipelines using PySpark to process and transform large datasets.
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AWS Integration: Utilize AWS services, including Athena and EMR, to manage and optimize data workflows and storage solutions.
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Data Management: Implement data quality, data governance, and data security best practices to ensure the integrity and confidentiality of data.
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Performance Optimization: Optimize and troubleshoot data processing workflows for performance, reliability, and scalability.
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Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
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Documentation: Create and maintain comprehensive documentation of data pipelines, ETL processes, and data architecture.
Requirements
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Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
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Experience: 5+ years of experience as a Data Engineer or in a similar role, with a strong emphasis on PySpark.
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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.
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Programming: Proficiency in Python; experience with other programming languages is a plus.
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Problem-Solving: Excellent analytical and problem-solving skills with attention to detail.
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Communication: Strong verbal and written communication skills to effectively collaborate with team members and stakeholders.
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Agility: Ability to work in a fast-paced, dynamic environment and adapt to changing priorities.
Preferred Qualifications:
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Experience with data warehousing solutions and BI tools.
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Knowledge of other big data technologies such as Hadoop, Hive, and Kafka.
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Understanding of data modeling, ETL processes, and data warehousing concepts.
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Experience with DevOps practices and tools for CI/CD.