- Design, build, and maintain scalable, reliable data pipelines using modern cloud-based orchestration frameworks
- Develop, test, and optimize analytics-ready data models using dbt and analytics engineering best practices
- Architect and maintain modern data lake and lakehouse storage patterns to support batch and streaming workloads
- Build and support batch and near–real-time data processing workflows using distributed processing frameworks
- Manage and optimize cloud data storage and compute services to ensure performance, scalability, and cost efficiency
- Establish and enforce data quality, testing, and governance standards, including dbt tests and documentation
- Collaborate with analytics, data science, application, and business teams to translate requirements into scalable data solutions
- Monitor data pipelines, troubleshoot data quality or performance issues, and improve system reliability
- Support CI/CD pipelines and infrastructure automation for data workflows and platforms
- Ensure data security, access controls, and governance best practices are followed
- Contribute to engineering best practices, documentation, and code reviews
- Evaluate and integrate tools and technologies that improve platform scalability, developer experience, and operational efficiency
- 5+ years of experience in data engineering or analytics engineering roles
- Strong proficiency in Python and SQL
- Hands-on experience designing and building data pipelines on AWS
- Experience with AWS data services such as S3, Glue, Redshift, RDS, Lambda, Athena, and related analytics tooling
- Strong experience with dbt for data transformations, testing, and analytics engineering workflows
- Experience with workflow orchestration frameworks (e.g., Airflow or similar tools)
- Experience working with distributed data processing technologies (e.g., Spark or similar)
- Experience designing or supporting modern data lake or lakehouse architectures
- Familiarity with streaming or messaging platforms (e.g., Kafka or cloud-native equivalents)
- Experience with infrastructure-as-code and containerization tools (e.g., Terraform, CloudFormation, Docker)
- Solid understanding of CI/CD concepts as applied to data systems
- Ability to communicate effectively with both technical and non-technical stakeholders
- Experience with streaming data platforms (e.g., Kinesis, Kafka)
- Exposure to analytics, BI, or visualization tools
- Experience in regulated or compliance-focused data environments
- Exposure to ML or AI-related data pipelines and feature generation use cases
- Experience supporting self-service analytics at scale
- Prior mentoring or informal technical leadership experience
- AWS certifications
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Data Engineer - Austin - IQ Clarity, LLC
Description
IQ Clarity's client is seeking a Data Engineer to design, build, and maintain scalable, cloud-based data platforms and pipelines. This role partners closely with engineering, analytics, and business stakeholders to ensure high-quality, reliable data is available for analytics, reporting, and advanced data use cases.
Responsibilities:
Requirements:
Nice to Have:
IQ Clarity, LLC is an Equal Opportunity Employer.
No C2C or third-party candidates
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Data Engineer, Applications Engineering Data
Only for registered members Austin, TX
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Data Engineer, Applications Engineering Data
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Data Engineer
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Data Engineer
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Data Engineer
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Data Engineer
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Data Engineer
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Data Engineer
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Data Engineer
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Data Engineer
Only for registered members Austin, Texas, , United States
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Data Engineer
Only for registered members Austin
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Data Engineer
Only for registered members Austin
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Data Engineer
Only for registered members Austin
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Data Engineer
Only for registered members Austin
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Data Engineer
Only for registered members Austin
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Data Engineering
Only for registered members Austin, TX
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Data Engineering
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Data Engineer
Only for registered members Austin
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Data Engineer
Only for registered members Austin
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Data Engineer
Only for registered members Austin