
Senior Data Engineer
1 week ago
- 7+ years of experience in data engineering or equivalent technical role.
- 5+ years of hands-on experience with AWS Cloud Development and DevOps.
- Strong expertise in SQL, data modeling, and ETL/ELT pipelines.
- Deep experience with Oracle (PL/SQL, performance tuning, data extraction).
- Proficiency in Python and/or Scala for data processing tasks.
- Strong knowledge of cloud infrastructure (networking, security, cost optimization).
- Experience with infrastructure as code (Terraform).
- Familiarity with CI/CD pipelines and DevOps tooling (e.g., Jenkins, GitHub Actions).
Roles and Responsibilities
- Data Engineering & Architecture
- Design, build, and maintain scalable data pipelines and data products.
- Develop and optimize ELT/ETL processes using a variety of data tools and technologies.
- Support and evolve data models that drive operational and analytical workloads.
- Modernize legacy Oracle-based systems and migrate workloads to cloud-native platforms.
- Cloud Development & DevOps (AWS-Focused)
- Build, deploy, and manage cloud-native data solutions using AWS services (e.g., S3, Lambda, Glue, EMR, Redshift, Athena, Step Functions).
- Implement CI/CD pipelines, IaC (e.g., Terraform or CloudFormation), and monitor cloud infrastructure for performance and cost optimization.
- Ensure data platform security, scalability, and resilience in the AWS cloud.
- Technical Leadership & Mentoring
- Act as a subject matter expert on cloud-based data development and DevOps best practices.
- Mentor data engineers on AWS architecture, infrastructure as code, and cloud-first design patterns.
- Participate in code and architecture reviews, enforcing best practices and high-quality standards.
- Cross-functional Collaboration
- Work closely with product managers, data analysts, software engineers, and other stakeholders to understand business needs and deliver end-to-end solutions.
- Support and evolve the roadmap for data platform modernization and new product delivery.
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