Data Engineer
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Job Description
Data Engineer building resilient data pipelines for Zeal, an AI-enabled software consultancy serving Fortune 1000 companies. Delivering migrations, transformations, governance, and production-ready data architectures.
Responsibilities:
- Gather and understand requirements for data migration and transformation
- Design, build, and maintain performant, resilient, and maintainable data pipelines
- Collaborate with stakeholders to ensure designs and implementations meet requirements and project standards
- Implement required data architectures and designs using appropriate tools
- Guide pipelines through testing, version control, CI/CD, review, and production deployment
- Monitor pipelines to ensure requirements and expectations are met
- Troubleshoot and remediate pipelines to maintain stability and effectiveness
- Document and transfer knowledge within the project team
- Maintain awareness of business, technical, and broader project requirements
- Participate actively in project meetings and discussions
- Provide input and feedback to architecture teams
- Ensure data quality, integrity, and availability across upstream and downstream systems
- Contribute to data governance and data-management best practices
Requirements:
- Strong SQL skills, including understanding of performance and parallelism
- At least one year of material experience on a traditional OLTP database such as Oracle, SQL Server, or Postgres
- At least one year of material experience on a modern MPP data platform such as Databricks, Snowflake, Azure Synapse, Redshift, or BigQuery
- Familiarity with cloud platforms, including basics of storage and security
- Material experience with at least one data transformation tool, such as Fivetran, Informatica, DataStage, dbt, or native cloud/data-platform tools
- Basic understanding of Medallion data architectures
- Basic skills with orchestration tools such as Airflow, source code control such as git, and CI/CD
- Effective writing and communication skills
- Ability to use AI tools to improve productivity
- Solid foundation in data engineering and keen interest in consulting
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