Senior Data Engineer
New
S
Sedona DigitalData Engineering
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonSQLSnowflakeData modeling
Requirements
- 5+ years of experience in data engineering, ETL/ELT, or data integration.
- Strong experience with AWS data services, including S3 and RDS.
- Hands-on experience with Snowflake, SQL, and data modelling.
- Proficiency in Python or a similar scripting language.
- Experience building and supporting scalable batch data pipelines.
- Experience integrating APIs, databases, SFTP locations, and file-based sources.
- Strong understanding of data transformation, validation, quality, and governance.
- Experience monitoring, troubleshooting, and optimising production data processes.
- Ability to work independently and take ownership of client-facing deliverables.
- Experience with SAS datasets and data-processing programs.
- Hold a valid Microsoft certification or commit to completing a relevant certification within three months of joining.
Responsibilities
- Design, build, and maintain scalable data pipelines and integration workflows using AWS, Snowflake, SQL, and Python.
- Manage data ingestion from APIs, databases, SFTP locations, and file-based sources.
- Build and optimise data models, transformations, and data-quality controls.
- Take ownership of recurring client processes, including the monthly SAS-based claims workflow.
- Monitor and troubleshoot pipelines, batch processes, and production data environments.
- Apply security, governance, access-control, and credential-management best practices.
- Improve pipeline resilience through effective monitoring, error handling, restartability, and recovery.
- Optimise data workloads for performance, scalability, and cost.
- Develop reusable components and patterns for ingestion, transformation, validation, and monitoring.
- Prepare governed and trusted datasets for analytics, reporting, AI, and machine-learning use cases.
- Collaborate with clients and internal stakeholders to translate business requirements into practical technical solutions.
- Identify opportunities to modernise legacy processes, reduce manual effort, and improve operational efficiency.
- Maintain technical documentation, data lineage, business rules, and operational runbooks.
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