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Data Engineer

Daman ConsultingPlano, TX🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationPlano, TX, United States
SQLGitAWSSnowflakeGitHub ActionsGitLab CIGoogle CloudPythondbtAzureCI/CD

Job description

Job Title: Data Engineer (Developer Role) – Snowflake, dbt, & Control-M

Job Location: Hybrid - Plano, TX or San Antonio, Texas

Job 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.

Required Skills:

• 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

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