Senior Data Engineer

Lead end-to-end data platform design and operational excellence for AssetMark’s Azure and Snowflake ecosystem.

Responsibilities

• Define, champion, and drive the technical vision for modern data architecture across Azure and Snowflake.
• Architect and implement highly scalable, resilient ELT/ETL pipelines for mission-critical financial workloads, with a focus on performance.
• Provide expert technical guidance during evaluation and selection of new data tools and frameworks, including orchestration, observability, and vector databases.
• Drive FinOps practices for the data platform, optimizing Snowflake compute, Azure storage, and cost per query efficiency.
• Act as a hands-on technical leader by writing, optimizing, and reviewing complex code primarily in Python and SQL.
• Define, document, and enforce engineering best practices, architectural design patterns, and coding standards across the data team.
• Oversee code reviews and provide constructive feedback to ensure code is scalable, secure, maintainable, and aligned to the target architecture.
• Mentor and coach junior and mid-level data engineers, including guidance on debugging complex distributed systems and modern data stack methodologies.
• Lead integration of data solutions into CI/CD pipelines using Azure DevOps and GitHub Actions, ensuring testing, deployment automation, and operational readiness.
• Own the strategy and implementation of Data Observability (example: Monte Carlo) to monitor health, freshness, volume, and lineage of production datasets.
• Ensure comprehensive data lineage is captured and maintained for transparency, auditing, and impact analysis.
• Partner with security and compliance teams to implement rigorous data governance policies, including PII masking, data tokenization, and RBAC tailored to financial data.
• Define, monitor, and enforce data SLAs and SLOs for critical data assets, and lead blameless post-mortems after data incidents.
• Collaborate with Data Science and Product teams 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 via Snowflake Cortex or open-source frameworks to automate engineering tasks and enable 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 focused on 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 track record leading technical design sessions, defining target-state architectures, and mentoring senior engineers.
• Strong experience with modern data stack tooling, 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 the ability to explain complex technical trade-offs to non-technical executive stakeholders.
• Direct experience required with Snowflake, DBT, Fivetran, and Azure data lake.
• Hybrid work schedule supported; must be close to the Charlotte, NC office.
• Must be legally authorized to work in the US; no visa sponsorship for this role.

Technologies

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

Compensation

• Base salary: $162,000-$190,000 USD per year
• 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