
Full Stack Data Engineer
4 weeks ago
Job Summary :
The role requires deep expertise in cloud-based data platforms, data warehousing, data lakehouse design, workflow automation, and data integration to support business intelligence and advanced analytics.
The ideal candidate will have a strong background in data engineering, cloud technologies, and full-stack software development, with a focus on performance optimization, security (especially data segregation), and automation.
Key Responsibilities :
- Develop and optimize data warehouse and data lakehouse architectures.
- Implement ETL/ELT processes, data modeling, and API integrations.
- Automate workflows and orchestrations using Airflow, Dagster, or Prefect.
- Ensure data quality, validation, governance, and compliance (GDPR, CCPA).
- Collaborate with cross-functional teams to support data-driven decision-making.
- Manage infrastructure with cloud services (AWS/Azure/GCP) and IaC tools like Contribute to CI/CD pipelines, DevOps practices, and containerization (Docker, Skills Required :
- Data Engineering & Warehousing : Snowflake (must have), DBT (must have), SnapLogic, ETL/ELT, APIs, Data Lakehouse Programming & Scripting : Advanced SQL, Python, DBT, Bash/Shell Cloud & Infrastructure : AWS, Azure, or GCP; Terraform; CloudFormation; Security (IAM, VPN, Data Processing & Orchestration : Kafka, Kinesis, Apache Airflow, Dagster, DevOps & CI/CD : Git, GitHub Actions, Jenkins, Docker, Data Governance & Quality : Data validation, metadata management, compliance with Profile :
- 5+ years of experience in data engineering and cloud platforms.
- Proven track record in end-to-end data pipeline development and automation.- Strong problem-solving, analytical, and communication skills.
- Ability to work independently in a remote-first environment
(ref:hirist.tech)-
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