Senior Data Engineer

Heitmeyer Consulting has a banking client that has a need within their Chief Data Office for a Senior Data Engineer who is highly hands‑on and experienced in building modern, scalable data pipelines and transformation frameworks using Snowflake and dbt . This role focuses on delivering high-quality, production‑grade data solutions with strong engineering discipline, leveraging Python , CI/CD , and Git‑based development practices . The ideal candidate brings deep, practical experience in dbt coding, Snowflake engineering, and Fivetran , along with a strong sense of ownership, accountability, and the ability to operate independently. Direct, hands‑on experience with Fivetran, dbt, and Snowflake is a mandatory screening requirement . Candidates without strong hands‑on experience across all three will not be considered. Role must be based in Dallas, TX. Top Required Skills 10+ years of experience in data engineering / analytics engineering roles. Strong hands‑on experience with dbt in production, including: Model development and dependency management Macro development and reusable frameworks Testing strategies (schema tests, custom tests) Deployment and environment management Strong Snowflake expertise, including: Data modeling and warehouse design Performance tuning and cost optimization Deep understanding of virtual warehouses, micro‑partitions, clustering, and query pruning Role‑based access control (RBAC) and secure data access Advanced SQL expertise with ability to build and optimize complex transformations. Strong Python programming skills for data engineering use cases. Proven experience with Git integration, including collaborative development workflows. Strong experience implementing CI/CD pipelines for data platforms and dbt deployments. Experience building and maintaining production‑grade data pipelines with SLAs, monitoring, and reliability standards. Mandatory requirement: direct, hands‑on experience with Fivetran, dbt, and Snowflake in production, including Fivetran connector setup and troubleshooting, dbt model development and testing, and Snowflake data engineering, performance tuning, and secure access patterns. This is a strict screening criterion. Nice‑to‑have Experience with Airflow / Astronomer or similar orchestration tools. Exposure to data governance, lineage, and observability tools. Financial services / banking domain experience is strongly preferred and will be prioritized, though not mandatory. Key Responsibilities Design, build, and maintain scalable ELT pipelines, leveraging Fivetran for ingestion and dbt for transformation on Snowflake. Direct hands‑on experience with Fivetran, dbt, and Snowflake is required for this role. Develop and maintain robust dbt projects, including: Modular models (staging, intermediate, marts) Reusable macros and Jinja templating Snapshots for SCD Type2 handling Schema and custom data quality tests Documentation using dbt docs Implement modular and reusable dbt architecture supporting multi‑environment deployments (dev, test, prod). Design and implement scalable data models using best practices (dimensional modeling, star schema, and data vault where applicable). Optimize Snowflake performance and cost efficiency, including: Query tuning and execution optimization Warehouse sizing and workload management Effective use of micro‑partitions, clustering, and pruning Build and enforce strong data quality and validation frameworks, including: Unit testing for transformations (dbt and custom frameworks) Data reconciliation and consistency checks Develop Python‑based solutions for automation, orchestration support, metadata‑driven processing, and operational tooling. Implement and enforce Git‑based development practices: Version control, branching strategies, pull requests, and code reviews Consistent and collaborative engineering workflows Build, maintain, and enhance CI/CD pipelines for dbt deployments: Automated build, test, and deployment processes Environment promotion (dev?test?prod) Integration with enterprise deployment pipelines Work with orchestration tools such as Airflow / Astronomer to schedule, monitor, and manage data pipeline execution (preferred). Collaborate closely with platform, governance, and business teams to align on data requirements, access control, and delivery expectations. Heitmeyer Consulting is an equal opportunity employer, and we encourage all qualified candidates to apply. Qualified applicants will be considered without regard to minority status, gender, disability, veteran status or any other characteristic protected by law. #J-18808-Ljbffr