Senior Data Engineer

Assetmark is seeking a Senior Data Engineer and technical lead to drive the end-to-end design, governance, and operational excellence of its data platform. This role focuses on hands-on leadership across scalable Azure and Snowflake architecture, with responsibilities that extend into data observability and the integration of AI/ML into the data ecosystem.

Based in Charlotte, NC with a hybrid work schedule, the successful candidate will help shape the technical vision, strengthen platform reliability for mission-critical workloads, and partner across engineering, security, compliance, data science, and product to deliver production-ready data capabilities.

Responsibilities

• Define, champion, and execute a modern data architecture technical vision across Azure and Snowflake.
• Architect and implement highly scalable, resilient ELT/ETL pipelines with performance tuned for mission-critical financial workloads.
• Provide technical guidance for evaluating and selecting new data tools and frameworks, including orchestration, observability, and vector databases.
• Drive FinOps practices by optimizing Snowflake compute usage, Azure storage costs, and overall cost-per-query efficiency.
• Lead by example through hands-on development, primarily using Python and SQL, including writing, optimizing, and reviewing complex code.
• Define, document, and enforce engineering best practices, architectural design patterns, and team coding standards.
• Oversee code review and deliver high-quality technical feedback to support scalability, security, maintainability, and alignment with the platform vision.
• Mentor junior and mid-level data engineers, including support for debugging complex distributed systems and modern data stack methodologies.
• Lead CI/CD integration for data solutions using tools such as Azure DevOps and GitHub Actions, ensuring robust testing, deployment automation, and operational readiness.
• Own data observability strategy and implementation (including Monte Carlo) to monitor health, freshness, volume, and lineage across production datasets.
• Ensure comprehensive data lineage is captured and maintained for transparency, auditing, and impact analysis.
• Collaborate with security and compliance teams on data governance policies, including PII masking, data tokenization, and RBAC for financial data.
• Define, monitor, and enforce data SLAs and SLOs, and lead blameless post-mortems following data incidents.
• Partner with Data Science and Product to design data flows and infrastructure supporting AI/ML training, inference, and MLOps.
• Provide technical leadership for piloting and implementing Generative AI (GenAI) using LLMs through tools like Snowflake Cortex or open-source frameworks to automate engineering tasks and enable new data products.
• Guide best practices for designing and curating versioned, high-quality feature sets for production-ready machine learning models.

Requirements

• 10+ years of progressive experience in Data Engineering or Software Engineering, with a significant portion dedicated to cloud data platforms.
• Expert proficiency in Python and Advanced SQL.
• Deep, hands-on experience with Snowflake (architecture, performance tuning, Snowpark) and Microsoft Azure data services.
• Proven experience leading technical design sessions, defining target-state architectures, and mentoring senior engineers.
• Strong experience with modern data stack tools, including dbt (Data Build Tool) and workflow orchestration (Airflow, Azure Data Factory).
• Experience working with large-scale, complex datasets, preferably in Financial Services or Asset Management.
• Exceptional communication skills, including articulating complex technical trade-offs to non-technical executive stakeholders.
• Direct experience with Snowflake, DBT, Fivetran, and Azure data lake is required.
• Ability to accommodate a hybrid work schedule and be close to the Charlotte, NC office.
• Must be legally authorized to work in the US. Visa sponsorship is not available for this position.

Technologies

• Azure, Snowflake, Azure Synapse, Azure Data Factory, Azure data lake
• DBT (Data Build Tool), Fivetran, Airflow, Monte Carlo
• Python, SQL, CI/CD
• Azure DevOps, GitHub Actions
• Role-Based Access Control (RBAC)
• AI/ML, MLOps, Generative AI (GenAI), LLMs, Snowflake Cortex
• Snowpark, vector databases, PII masking, data tokenization

Compensation

The base salary range for this position is $162,000 to $190,000 per year. This role may also be eligible for additional variable incentive compensation and competitive benefits.

Benefits

• Flex Time or Paid Time Off and Sick Time Off
• 401K with 6% Employer Match
• Medical, Dental, Vision (HDHP or PPO)
• HSA employer contribution (HDHP only)
• Volunteer Time Off
• Career Development / Recognition
• Fitness Reimbursement
• Hybrid Work Schedule