Senior Data Engineer

Assetmark is hiring a Senior Data Engineer / Technical Lead to help build and operate a modern data platform across Azure and Snowflake. This role combines hands-on engineering with technical leadership, including data governance, operational excellence, FinOps, and the integration of AI/ML and GenAI capabilities into production data flows.

What you’ll do

• Define and drive the technical vision for modern data architecture spanning Azure and Snowflake.
• Design and implement scalable, resilient ELT/ETL pipelines to support mission-critical financial workloads.
• Lead technical evaluations and selection of new data tools and frameworks, including orchestration, observability, and vector databases.
• Own FinOps practices to optimize Snowflake compute usage, Azure storage costs, and improve cost-per-query efficiency.
• Write, optimize, and review complex code primarily in Python and SQL, with a focus on scalability, security, and maintainability.
• Define and enforce engineering best practices, architectural design patterns, and coding standards across the data team.
• Guide code review with high-quality, constructive feedback to keep engineering aligned with the defined architecture and vision.
• Mentor junior and mid-level data engineers, including debugging complex distributed systems and applying modern data stack methodologies.
• Lead CI/CD integration for data solutions using tools like Azure DevOps and GitHub Actions, ensuring testing, deployment automation, and operational readiness.
• Implement data observability (for example, Monte Carlo) to monitor dataset health, freshness, volume, and lineage.
• Ensure comprehensive data lineage is captured and maintained to support transparency, auditing, and impact analysis.
• Collaborate with security and compliance teams to design data governance policies such as PII masking, data tokenization, and RBAC for financial data.
• Define, monitor, and enforce data SLAs and SLOs, and lead blameless post-mortems after data incidents.
• Partner with Data Science and Product teams on data flows and infrastructure for AI/ML training, inference, and MLOps.
• Provide technical leadership in piloting and implementing GenAI, including LLM-based tooling through platforms such as Snowflake Cortex and open-source frameworks.
• Guide the design and curation of versioned, production-ready feature sets for machine learning models.

What you bring

• 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 ability to lead technical design sessions, define target-state architectures, and mentor senior engineers.
• Strong experience with modern data stack tools, including dbt and workflow orchestration tools such as Airflow and Azure Data Factory.
• Experience working with large-scale, complex datasets, preferably in Financial Services or Asset Management.
• Exceptional communication skills, including the ability to explain complex technical trade-offs to non-technical executive stakeholders.
• Direct experience with Snowflake, dbt, Fivetran, and Azure data lake.
• 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.

Compensation & benefits

Salary range: $162,000 - $190,000 base salary (yearly). This position may also include additional variable incentive compensation and competitive 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