Senior Manager - Data Engineering - Magna Legal Services

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:

Snowflake Platform

• 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.

dbt & Transformation Layer

• 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.

Azure Data Ecosystem

• 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.

Team Leadership

• 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.

Standards & Governance

• Define and enforce organization-wide ETL/ELT best practices, naming conventions, and code review standards.
• Champion d