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Today

Senior Data Engineer

CMG Financial United States

United States

Today

$130k - $165k/yr Full time Senior Application Security Cdc

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Job Description

CMG Financial is hiring a Senior Data Engineer (onsite in the United States) to build and operate a governed, Snowflake-based Enterprise Data Warehouse platform.

Responsibilities

Build and operate Snowflake ingestion from on-premises SQL Server systems (including BytePro) and from SaaS/vendor sources.
Use Fivetran, CDC / Change Tracking, Azure Data Factory, and vendor data shares for ingestion.
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 Raw and Bronze layers.
Support Silver layer contracts built by domain teams.
Manage Snowflake as code with Pulumi (TypeScript), including databases, roles, grants, warehouses, service users, and policies.
Provision Azure resources with Terraform.
Deploy via GitHub Actions with reviewed, gated promotion across DEV, QA, UAT, and PROD.
Implement access controls using RBAC, tag-based column classification, and dynamic masking.
Create least-privilege service accounts with key-pair authentication and just-in-time elevation for sensitive data under GLBA, FCRA, and HMDA obligations.
Ensure approvals for sensitive access are recorded and auditable.
Build freshness, volume, and schema checks, including alerting and runbooks.
Detect and remediate silent failures such as stalled pipes, stale grants, and untagged objects before consumers are impacted.
Contribute to specs and ADRs, write clear PRs, and participate in rigorous code review.
Measure before asserting and maintain a verifiable trail for changes and outcomes.
Partner with Servicing, Lending, and Marketing data owners, plus Domo and BI developers during the SDW to EDW migration, including parallel-run reconciliation.
Mentor engineers and raise standards for testing, automation, and documentation.

Requirements

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 with tests.
Hands-on dbt experience in production (modeling, testing, CI, and environments).
Experience with a modern orchestrator: Dagster, Airflow, or Prefect.
Hands-on managed ingestion or CDC: Fivetran or similar.
Infrastructure-as-code experience: Pulumi, Terraform, or similar; CI/CD with GitHub Actions or Azure DevOps.
Snowflake security depth: RBAC, masking, row-access policies, tags, service authentication, and cost-aware warehouse management.
Working knowledge of SQL Server source systems: CDC and Change Tracking, plus ability to read execution plans with a DBA team.
Experience handling regulated or sensitive data (e.g., PII and financial data) with auditable controls.
Clear written communication: ability to write specs, PR descriptions, and incident notes.

Technologies

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

Nice to Have

Mortgage, lending, or loan-servicing domain experience (origination, servicing, investor reporting).
Azure experience: 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 (OpenMetadata / DataHub or similar).
Experience migrating SSIS packages or legacy ETL onto modern tooling.
Domo or other BI platforms as downstream warehouse consumers.
Experience using AI coding assistants responsibly in a reviewed engineering workflow.
Streaming/event-driven data: Kafka (or Azure Event Hubs), change-data streams, and Snowflake streaming ingestion (Snowpipe Streaming) alongside batch pipelines.
Durable workflow orchestration and containers: Temporal (CMG adoption) and Kubernetes for running containerized services.
Data modeling experience with Inmon, Kimball, Medallion (Bronze / Silver / Gold), or Data Vault 2.0.
Experience with AI-Driven Development Lifecycle (AI-DLC) using a structured, human-governed, intent-to-deployment workflow with engineer-checked approvals.

How We Work

Changes land through reviewed pull requests, with production changes using approval gates.
Governance rules are documented as specs and ADRs and enforced in code and CI (access decisions driven by reviewed rules).
Prioritize measuring over assuming, fixing root causes over workarounds, and owning issues until closure.

Supervisory Responsibilities

Direct Reports: N/A

Physical and Environmental Conditions

Operates in an ADA compliant office environment using typical office equipment and computer-based work.
May involve partial stationary positions and moving throughout the day.
Overtime may be required to meet project deadlines.

Compensation

Annual Salary: $130,000 - $165,000
Actual compensation determined based on relevant data engineering experience, IT background, mortgage industry depth, technical skills, education, and other job-related qualifications.

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