Manage and grow a data engineering team, overseeing the design and maintenance of data platforms using Snowflake, dbt, and Azure. Drive best practices in data management and ensure reliable data movement and quality.
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: Senior Manager - Data Engineering
Position Summary:
This role will continue building and maturing our data platform. We have made meaningful investments in our Snowflake-based architecture and dbt modeling layer, and we are looking for a leader who can accelerate that momentum — raising the quality bar on our data models, expanding coverage across new domains, and establishing the conventions and processes that will carry the platform forward as the business grows.
You will lead a team of data engineers, own the technical roadmap for our cloud data stack (Snowflake, Azure, dbt), and partner closely with analytics, product, and operations stakeholders to turn raw data into reliable, well-modeled assets that teams can trust and build on. This is a hands-on leadership role — the ideal candidate is equally comfortable reviewing a dbt PR, designing a new data model, and running a team planning session.
Key Responsibilities:
- Serve as the internal authority on Snowflake architecture, performance tuning, cost governance, and security (RBAC, data masking, network policies).
- Design and maintain a scalable, well-documented warehouse structure including database, schema, and object hierarchy standards.
- Drive Snowflake feature adoption — dynamic tables, Snowpark, data sharing, and emerging capabilities.
- Own the dbt project end-to-end: modeling conventions, testing strategy, documentation standards, and CI/CD integration.
- Establish and enforce a layered modeling approach (staging → intermediate → marts) that downstream teams can trust and self-serve.
- Lead the design and operation of data pipelines on Azure, including Azure Data Factory
- Ensure reliable, monitored data movement from source systems into Snowflake with clear SLAs and alerting.
- Manage, mentor, and grow a team of data engineers — running regular 1:1s, setting performance goals, and building a culture of engineering excellence.
- Own hiring, onboarding, and career development for the data engineering function.
- Translate business requirements from stakeholders into well-scoped, prioritized engineering work.
- Define and enforce organization-wide ETL/ELT best practices, naming conventions, and code review standards.
- Champion data quality, observability (e.g., dbt tests), and lineage across the platform.
- Proactively identify opportunities for data process improvements and lead initiatives to implement these changes.
Snowflake Platform
dbt & Transformation Layer
Azure Data Ecosystem
Team Leadership
Standards & Governance
Qualifications:
Bachelor’s degree in computer science, Information Technology, Engineering, or a related field
7+ years in data engineering, with at least 2 years in a team lead or management role
Deep, production-grade Snowflake expertise — you have designed warehouse architectures, optimized query performance, managed costs, and implemented enterprise security controls
Fluency with dbt: you have built and maintained dbt projects at scale and can articulate opinionated best practices
Hands-on Azure Data Factory experience
Strong SQL skills and proficiency in Python for data pipeline development and automation
Proven ability to lead and grow a small team while remaining technically engaged
Strong communicator who can translate complex data concepts to non-technical stakeholders and contribute to strategic planning conversations
Nice to have:
Familiarity with data observability tooling (Elementary, Monte Carlo, or similar).
Exposure to Snowflake Cortex, Snowpark ML, or other AI/ML capabilities on Snowflake
Experience in a high-growth or scale-up environment where standards were built from the ground up
Compensation: USD $140,000 - $170,000 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.
Similar Jobs
Cloud • Information Technology • Software
Lead the Data Engineering practice as a senior pillar head: drive strategy, grow accounts, oversee solution architecture and delivery across Snowflake/Databricks/cloud platforms, develop offerings, mentor senior teams, and ensure governance, quality, and commercial performance for enterprise data modernization programs.
Top Skills:
AWSAzureBigQueryDatabricksEtl/EltMicrosoft FabricSnowflake
HR Tech • Legal Tech • Software • Consulting
Lead the Data & Cloud Platform for the AI organization, building cloud runtime, unified data access layers, agent memory/context systems, and data ingestion/transformation pipelines. Split time between hands-on engineering and managing a small team, set platform patterns, ensure privacy-aware data handling, and partner with product and governance teams to scale maintainable, cost-effective infrastructure for AI workloads.
Top Skills:
Agent MemoryAWSCi/CdDbtEltETLFivetranLakehouseLlmOciPythonSemantic SearchSnowflakeTypescript
AdTech • Marketing Tech
Lead teams building and operating the core data platform, ingestion pipelines, datalake adoption, Data APIs, permissions, and customer-facing data access to enable reliable, scalable client data delivery and AI-enabled workflows; partner cross-functionally and develop engineering talent while reducing operational burden through automation.
Top Skills:
Ai-Enabled WorkflowsAPIsCli ToolingData ApisData PipelinesDatalakeLlm ToolingPermissions Systems
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
