Senior Data Engineer

CMG Financial is seeking a Senior Data Engineer (onsite in the United States) to build and operate a governed, Snowflake-based Enterprise Data Warehouse platform. The role covers the full path from source to consumer, including ingestion, orchestration, transformation, and security and governance for regulated data.

Role Overview

This position owns pipelines and platform components end to end, with a focus on access control and auditable handling of sensitive and regulated information. Work spans on-premises and SaaS ingestion, modern orchestration, dbt transformations, and infrastructure-as-code deployments across DEV, QA, UAT, and PROD.

Key Responsibilities

• Build and operate ingestion from on-premises SQL Server systems, including the BytePro loan-origination system, and from SaaS and vendor sources into Snowflake using Fivetran, CDC / Change Tracking, Azure Data Factory, and vendor data shares.
• Develop and maintain Dagster (Dagster+) assets, schedules, sensors, and checks in Python.
• Migrate remaining GitHub Actions-run and legacy SSIS jobs onto the orchestration platform.
• Write and review dbt models, tests, seeds, and snapshots for the Raw and Bronze layers, along with contracts domain teams build on for Silver.
• Manage Snowflake as code using Pulumi (TypeScript) for databases, roles, grants, warehouses, service users, and policies; use Terraform for Azure resources; and deploy through GitHub Actions with reviewed, gated promotion across DEV, QA, UAT, and PROD.
• Implement role-based access, tag-based column classification, and dynamic masking.
• Build least-privilege service accounts with key-pair authentication and enable just-in-time elevation for sensitive data under GLBA, FCRA, and HMDA obligations, with approvals recorded and auditable.
• Build freshness, volume, and schema checks, alerting, and runbooks.
• Investigate and resolve silent failures such as stalled pipelines, stale grants, and untagged objects before downstream consumers encounter issues.
• Contribute to specifications and ADRs, write clear PRs, and participate in rigorous code review.
• Measure before asserting and maintain a verifiable trail of work and outcomes.
• Partner with Servicing, Lending, and Marketing data owners and collaborate with Domo and BI developers during the SDW-to-EDW migration, including parallel-run reconciliation against the legacy system.
• Mentor engineers on testing, automation, and documentation practices.

Required Qualifications

• 7+ years in data engineering, including 3+ years building production pipelines on a cloud data warehouse (Snowflake preferred).
• Expert SQL and strong Python for pipeline and platform code, including tests.
• Hands-on dbt experience in production, covering modeling, testing, CI, and environments.
• Experience with a modern orchestrator (Dagster, Airflow, or Prefect) and managed ingestion or CDC (such as Fivetran).
• Infrastructure-as-code experience (Pulumi, Terraform, or similar) and CI/CD using GitHub Actions or Azure DevOps.
• Snowflake security depth: RBAC design, masking and row-access policies, tags, service authentication, and cost-aware warehouse management.
• Working knowledge of SQL Server as a source system: CDC and Change Tracking, plus ability to work effectively with a DBA using execution plans.
• Experience handling regulated or sensitive data (PII and financial data) with auditable controls.
• Clear written communication, including writing a spec, PR description, and incident note.

Technologies

• Snowflake, SQL, Python, Fivetran, CDC / Change Tracking, Azure Data Factory
• Dagster, Dagster+, dbt
• Pulumi, TypeScript, Terraform, GitHub Actions
• SSIS, BytePro
• GLBA, FCRA, HMDA
• SQL Server, Key-pair authentication, RBAC, Dynamic masking, Row-access policies, Tags
• Azure DevOps, Airflow, Prefect, Azure resources, Domo

Nice to Have

• Mortgage, lending, or loan-servicing domain experience (origination, servicing, investor reporting).
• Azure experience including Data Factory, ADLS, Key Vault, Entra ID groups, and SCIM provisioning.
• Snowflake Iceberg / catalog-linked tables, secure data sharing, and reader accounts.
• Data catalog and lineage tooling such as OpenMetadata / DataHub (or similar).
• Experience migrating SSIS packages or legacy ETL onto modern tooling.
• Domo or other BI platforms as downstream consumers of the warehouse.
• Responsible use of AI coding assistants within a reviewed engineering workflow.
• Streaming and event-driven data experience including Kafka (or Azure Event Hubs), change-data streams, and Snowflake streaming ingestion (Snowpipe Streaming) alongside batch pipelines.
• Experience with Temporal (CMG is adopting it and this role will integrate the data platform with it) and/or Kubernetes for containerized services.
• Data modeling experience with approaches such as Inmon, Kimball, Medallion, or Data Vault 2.0 and judgment to apply the right model per layer.
• Experience using AI-Driven Development Lifecycle (AI-DLC) workflows where steps are checked and approved by engineers before deployment.

How CMG Financial Works

• Changes land through reviewed pull requests, and production changes go through approval gates.
• Governance rules are written down as specs and ADRs, enforced in code and CI, and used to determine column-level access through reviewed rules rather than one-off grants.
• Teams value measuring over assumptions, fixing root causes over workarounds, and owning issues until they are fully closed.

Supervisory Responsibilities

Direct Reports: N/A

Physical and Environmental Conditions

• Operates in an ADA compliant office environment using typical office equipment and tasks including computer work.
• May involve partial stationary positions and moving throughout the day.
• Flexibility to work overtime to meet project deadlines is required.

Compensation

• Annual Salary: USD 130,000 - 165,000
• Actual compensation will be determined based on relevant data engineering experience, information technology experience, depth of mortgage industry experience, technical skills, education, and other job-related qualifications.

Location

United States: Onsite