Senior Data Engineer

Job Description:

Senior Data Engineer Experience

Required:

10+ Years

Location:

Richardson

Key Responsibilities Design, build, and optimize scalable data pipelines and ETL/ELT workflows to ingest, transform, and load data from multiple source systems into Snowflake. Develop, maintain, and enhance data transformation logic using DBT Cloud following best practices (modularity, testing, documentation, CI/CD). Build and manage integrations using Snap Logic or equivalent ETL/iPaaS tools (Informatica, Talend, Matillion, Fivetran, etc.) for batch and near real-time data movement.

Write and optimize complex SQL queries, stored procedures, and Snowflake-specific features (streams, tasks, materialized views, clustering, warehouses sizing) for performance and cost efficiency. Knowledge on data models (dimensional/star schema, Data Vault, or 3NF) and contribute to building a semantic layer for consistent, governed reporting across BI tools. Collaborate with data analysts, BI developers, and business stakeholders to translate requirements into reliable, well-documented data solutions.

Implement data quality checks, validation frameworks, and monitoring/alerting for pipeline reliability. Manage version control, CI/CD deployment pipelines for DBT models and ETL jobs (Git, Git Hub Actions/Azure Dev Ops/Jenkins). Optimize Snowflake performance and cost through query tuning, warehouse right-sizing, and efficient storage/partitioning strategies. Document data flows, transformation logic, and semantic layer definitions for maintainability and knowledge transfer. Mentor junior data engineers and enforce engineering best practices and coding standards.

Required

Skills & Qualifications 10+ years of experience in Data Engineering, ETL/ELT development, or Data Warehousing. Strong hands-on expertise with Snowflake (architecture, performance tuning, security, cost optimization). Proven experience with DBT Cloud (models, macros, tests, jobs, snapshots, documentation, CI/CD integration).

Experience with Snap Logic or comparable ETL/integration tools (Informatica, Talend, Matillion, Fivetran, Azure Data Factory, etc.). Advanced/Complex SQL skills — window functions, CTEs, query optimization, performance tuning. Strong understanding of data modeling concepts (dimensional modeling, Data Vault, normalization) and experience building/maintaining a semantic layer. Solid grasp of ELT/ETL design patterns, data pipeline orchestration (Airflow, dbt Cloud jobs, or similar).

Experience with cloud platforms (AWS/Azure/GCP) and cloud-native data architecture. Proficiency in scripting/programming (Python preferred) for automation and data processing. Familiarity with version control (Git) and CI/CD practices for data engineering workflows. Strong analytical, problem-solving, and communication skills; ability to work with cross-functional teams. Preferred / Good-to-Have Skills

Experience with BI/reporting tools (Tableau, Power BI, Looker) and their integration with a semantic layer. Knowledge of data governance, data cataloging, and metadata management tools. Exposure to real-time/streaming data (Kafka, Snowpipe Streaming). Snowflake certification (Snow Pro Core/Advanced) is a plus. Experience in Agile/Scrum delivery environments. Education Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent practical experience).