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Artificial Intelligence • Fintech • Information Technology • Machine Learning • Financial Services
The Data Engineer will design and build scalable data systems, contribute to the architecture of the data platform, and collaborate with AI/ML engineers to enhance automation and intelligence in Canoe's systems.
Top Skills:
AirflowAWSDbtKafkaPostgresRedshiftSnowflakeSQL
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
The Principal Data Engineer will lead data engineering efforts on public cloud, design scalable solutions, build data pipelines, and drive deliverables with a high level of technical expertise in relevant technologies.
Top Skills:
AdfAzureCi/CdContainersDatabricksDelta LakeDockerJenkinsKafkaSnowflakeSparkTerraform
Fintech • Machine Learning • Payments • Software • Financial Services
The Senior Distinguished Data Engineer will architect and deliver data solutions for Compliance and AML, mentor talent, and drive modern tech adoption.
Top Skills:
AWSPythonScalaSQL
About Us:
Magna Legal Services provides end-to-end legal support services to law firms, corporations, and governmental agencies throughout the nation. As an end-to-end service provider, we can provide strategic advantages to our clients by offering legal support services at every stage of their legal proceedings.
Job Description:
Job Title: Data Engineer
Position Summary:
Magna Legal Services is seeking a Data Engineer to lead the design, security, and scalability of our Snowflake data platform. This role will play a critical part in building enterprise-grade data models, enforcing best practices, and enabling analytics and AI use cases through a secure, high-performing data foundation. You'll help shape a secure, scalable data platform that powers analytics, reporting, and AI across the organization — while setting standards that allow the data team to grow sustainably.
Key Responsibilities:
- Design, own, and maintain core enterprise data models.
- Provide architectural leadership by defining and enforcing data engineering standards and best practices.
- Implement and manage Snowflake security and RBAC, ensuring secure, scalable access across analytics and AI use cases.
- Build and maintain reusable dbt macros, seeds, and utility functions.
- Leverage advanced dbt features including incremental models, snapshots, and exposures.
- Optimize and refactor complex SQL for performance, reliability, and maintainability.
- Implement and maintain CI/CD workflows (Git branching, automated testing, code reviews).
- Monitor Snowflake warehouse and query performance.
- Drive Snowflake cost optimization initiatives (warehouse sizing, caching, workload management).
- Mentor and support junior data engineering resources.
- Partner with leadership to co-own Snowflake COE and data governance practices.
Qualifications:
- 5+ years of experience in data engineering or analytics engineering.
- Deep hands-on experience with Snowflake, including performance tuning and RBAC.
- Strong production experience with dbt.
- Advanced SQL skills with a focus on optimization.
- Experience implementing CI/CD pipelines for data teams.
- Ability to design scalable, reusable data architectures.
- Strong communication skills and comfort working cross-functionally.
Nice to have:
- Experience with enterprise data governance or COE models.
- Exposure to AI/ML data enablement.
- Experience managing cloud data platform costs.
Compensation: USD $130,000 - $150,000 per year.
An employee’s pay position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, travel requirements, revenue-based metrics, any contractual agreements, and business or organizational needs. The range listed is just one component of the total compensation package for employees.
Magna Legal Services provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
