Data Engineer II
Data Engineer II
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Job Description
Job Description:
The Data Engineer will lead the design and architecture of AWSbased data solutions develop endtoend data pipelines manage data lakes and optimize data platforms for performance and scalability. Responsibilities include writing and testing Python SQL or other code conducting code reviews implementing end to end ETL/ELT processes enforcing data governance policies and driving innovation in data engineering practices. This role also involves collaboration with crossfunctional teams aligning with stakeholders on technical requirements providing technical leadership and mentoring team members to enhance overall team efficiency.
Key Responsibilities:
- Design and implement scalable data solutions on AWS including data lakes warehouses and streaming systems.
- Develop optimize and maintain data pipelines using AWS services.
- Implement robust ETL/ELT processes and eventdriven data ingestion.
- Establish and enforce data governance policies ensuring data quality security and compliance.
- Optimize cloud resources for performance availability and costefficiency.
- Partner with crossfunctional teams to gather requirements and deliver comprehensive cloudbased solutions.
- Identify opportunities to enhance systems processes and technologies while troubleshooting complex technical challenges.
Our current techstack:
- AWS: Glue Lambda Step Function Batch ECS Quicksight Machine Learning Sagemaker etc.
- DevOps: Cloudformation Terraform Git CodeBuild
- Database: Redshift PostgreSQL DynamoDB Athena
- Language: Bash Python SQL
Qualifications:
- Bachelors degree in Computer Science Engineering or related field. Masters degree preferred.
- Expertise in AWS platforms including data services. Basic knowledge of Azure is preferred.
- Extensive experience in data and cloud engineering roles.
- Expertise in AWS platforms including data services.
- Strong competence in ETL processes data warehousing and big data technologies.
- Advanced skills in scripting Python SQL and infrastructure automation tools.
- Familiarity with containerization (e.g. Docker) and orchestration (e.g. Kubernetes).
- Experience with data visualization tools (e.g. QuickSight) is a plus.
Employment Type
Full-Time
