Data Engineer

Harnham; Austin (TX); Hybrid; USD 150,000 - 165,000; Full time

Job summary

Harnham is seeking a Mid-Senior Data Engineer to help build a modern cloud-based data platform. This hybrid role offers ownership across the full data lifecycle, from ingestion to operations, in a growth-focused wealth management setting.

You will work with engineering, analytics, and business teams to deliver scalable data solutions, with emphasis on data modeling, platform reliability, and performance improvements. Location options include Miami or Austin, with hybrid work arrangements.

Qualifications

• Strong hands-on experience with Python and SQL.
• Proven experience building and maintaining data pipelines and data ingestion frameworks.
• Strong experience with dbt and modern data transformation practices.
• Experience with Azure cloud technologies and enterprise data platforms; data modeling and lifecycle management understood.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ingestion frameworks across multiple data sources.
• Build and optimize data models to support analytics, reporting, and downstream applications.
• Develop and enhance cloud-based data platform infrastructure focused on scalability, reliability, and performance.
• Utilize Python, SQL, and dbt to create robust data solutions.
• Implement and improve monitoring, data quality, and operational processes for platform reliability.
• Collaborate with cross-functional stakeholders to deliver high-quality data products and solutions.
• Troubleshoot production data issues and contribute to long-term data architecture roadmap.

Skills

Python

Data pipeline development

SQL

Education

Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or related field

Tools

dbt

Azure

Job description

Location: Miami, FL or Austin, TX (Hybrid)

Pay: $150k - $165k Base Salary + Bonus

No Sponsorship Available

About the Opportunity

A growing wealth management firm is seeking a Mid-Senior level Data Engineer to help build and evolve a modern cloud-based data platform. This is a highly visible, hands-on role offering significant ownership across the full data lifecycle, including data ingestion, transformation, modeling, platform development, and operational support.

The successful candidate will work closely with engineering, analytics, and business teams to deliver scalable and reliable data solutions that support critical organizational initiatives.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ingestion frameworks across multiple data sources.
• Build and optimize data models to support analytics, reporting, and downstream applications.
• Develop and enhance cloud-based data platform infrastructure with a focus on scalability, reliability, and performance.
• Utilize Python, SQL, and dbt to create robust and maintainable data solutions.
• Implement and improve monitoring, data quality, operational processes, and platform reliability.
• Collaborate with cross-functional stakeholders to deliver high-quality data products and solutions.
• Troubleshoot complex production data issues and contribute to the long-term data architecture roadmap.

Must-Have Qualifications

• 3+ years of experience in Data Engineering or a related data-focused engineering role.
• Strong hands-on experience with Python and SQL.
• Proven experience building and maintaining data pipelines and data ingestion frameworks.
• Strong experience with dbt and modern data transformation practices.
• Experience working with Azure cloud technologies and enterprise data platforms.Solid understanding of data modeling, data architecture, and data lifecycle management.
• Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative discipline.