Senior Data Engineer
2 months ago
MUST BE ONSITE HYBRID IN IRVINE 3 DAYS A WEEK
The Senior Data Engineer will be responsible for designing, developing, and maintaining robust data pipelines and architectures. This role requires deep expertise in Python, SQL, AWS, and modern ETL processes, with a strong emphasis on using Pandas and PySpark. The ideal candidate will have experience working with data lakes and PostgreSQL, and will excel in a dynamic, fast-paced environment.
Key Responsibilities:
- Design, build, and optimize scalable data pipelines and architectures to support data integration, processing, and analytics.
- Utilize Pandas, PySpark, and SQL to perform data transformations, cleaning, and analysis.
- Implement and maintain data solutions on AWS, leveraging services such as S3, Redshift, Glue, and Lambda.
- Develop and manage ETL processes to ensure efficient data flow and high data quality.
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and translate them into technical solutions.
- Monitor and troubleshoot data pipelines to ensure performance, reliability, and scalability.
- Ensure data integrity and security through best practices in data governance.
- Participate in code reviews, provide technical guidance, and mentor junior engineers.
- Stay current with emerging technologies and industry trends, integrating new solutions as appropriate.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Minimum of 5 years of experience in data engineering.
- Expertise in Python programming, with extensive experience using Pandas and PySpark.
- Strong proficiency in SQL and experience with relational databases such as PostgreSQL.
- Solid experience with AWS services, particularly for data engineering tasks.
- Proven experience with modern ETL processes and tools.
- Familiarity with data lake architectures and their implementation.
- Python and SQL.
- Strong problem-solving skills and the ability to work in a fast-paced, dynamic environment.
- Excellent communication and collaboration skills.
Preferred Qualifications:
- Experience with PSQL or other advanced SQL databases.
- Knowledge of data warehousing solutions and practices.
- Familiarity with data visualization tools and techniques.
- Certification in AWS (e.g., AWS Certified Data Analytics, AWS Certified Solutions Architect).
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