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# Data Engineer

- **Company:** Daman Consulting
- **Location:** Plano, TX, United States
- **Contract:** Contract
- **Skills:** Query Performance, Application Programming Interfaces (APIs), Amazon S3, ARM Architecture, Automation of Tests, Cloud Computing, Cloud Storage, Software Quality, Continuous Integration, Data Validation, Data Integrity, Extract Transform Load (ETL), Data Mart, Data Transformation, Data Warehousing, Software Debugging, DevOps, Github, Jinja (Template Engine), Python (Programming Language), Performance Tuning, Raw Data, Role-Based Access Control, Software Construction, Software Engineering, SQL Databases, Data Streaming, Workflow Management Systems, Data Processing, Cloud Platform System, Macros, Sql Optimization, Snowflake, Git, Data Layers, Gitlab-ci, Data Pipelines, Control M
- **Published:** November 7, 2026
- **Apply:** https://www.dice.com/job-detail/c11bb3ca-ead5-4a23-a99b-8e4d18b0ccdf

## About the Role

* Snowflake: Deep developer-level expertise including Snowpipe, Cortex Code, bulk data loading (COPY commands), streams, tasks, role-based access control (RBAC), and query performance optimization. Worked on cost understanding and estimations to reduce/improve Snowflake costs incurred by the jobs.

 * dbt (Core or Cloud): Strong operational knowledge of core concepts like snapshots, seeds, incremental models, tests, sources, and documentation.

 * Advanced SQL: Absolute mastery of SQL, including CTEs, analytical/window functions, complex joins, and aggregations.

 * Orchestration: Hands-on experience creating jobs, scheduling, managing dependencies, and debugging in Control-M.

 * DevOps / CI/CD: Solid understanding of Git version control (branching, PR reviews) and active experience building or managing continuous integration and continuous deployment (CI/CD) pipelines.

Preferred / Good-to-Have Qualifications

 * Proficiency in Python for general data processing utilities, automated scripting, or API interactions.

 * Familiarity with cloud ecosystems (AWS S3, Azure Blob, or Google Cloud Storage, Streaming concepts).

 * Background in dimensional data modeling or structural warehousing practices (SCD Type 1/Type 2 design).

 * Active Snowflake (SnowPro Core/Advanced) or dbt Developer

## Description

We are seeking a highly skilled and hands-on Data Engineer with strong software development fundamentals to design, build, and optimize scalable ELT data pipelines. In this developer-centric role, you will be responsible for turning raw data into production-ready data layers using Snowflake and dbt, orchestrating complex workflows via

Control-M, and ensuring seamless code quality and deployments through automated CI/CD pipelines. You will collaborate closely with data architects, analysts, and business stakeholders to maintain a modern data stack that adheres to software engineering best practices.

Responsibilities:

 * Pipeline Development: Design, build, and maintain modular, high-performance ELT data pipelines across staging, intermediate, and data mart layers.

 * Data Transformation: Write clean, advanced SQL and develop modular dbt models, reusable macros, packages, and Jinja templates.

 * Database Engineering: Create and configure Snowflake objects (tables, views, streams, tasks, stages) while utilizing advanced performance features like Time Travel, zero-copy cloning, and warehouse configurations.

 * Workflow Orchestration: Define, schedule, monitor, and troubleshoot enterprise-level batch and real-time data pipelines using Control-M. CI/CD Automation: Integrate dbt and Snowflake deployments into automated CI/CD pipelines (e.g., GitHub Actions, GitLab CI) to ensure seamless automated testing, pull request checks, and environment promotions.

 * Data Quality & Testing: Implement robust, automated data validation, schema testing, and monitoring metrics within dbt to enforce data integrity.

 * Performance Tuning: Optimize slow-running SQL queries, tune Snowflake virtual warehouse workloads, and streamline cluster usage for maximum cost efficiency.