Senior Data Engineer

Artech LLC

  • Dallas, TX
  • 1 day ago
  • $65–$68 Per Hour

Highlights

The ideal candidate will have deep expertise in Snowflake, DBT, Python, PySpark, Qlik Replicate, Astronomer Airflow, and CI/CD to develop scalable, secure, and high-performance data pipelines supporting modern analytics and business intelligence initiatives. The successful candidate will play a key role in architecting data ingestion frameworks, implementing data governance and security, managing schema evolution, and optimizing cloud-based data platforms.

Numbers & Facts

LocationDallas, TX
Salary$65–$68 Per Hour

Description

Request ID: 101192-1
Title: Senior Data Engineer
Locations: Raleigh/Phoenix/Dallas

Duration: 06+ Months with Possible Extension.
Pay Range: $65-$68/Hour on W2/C2C (All inclusive)


We are seeking a highly skilled Senior Data Engineer with 8 12+ years of experience in designing and building enterprise-scale data platforms. The ideal candidate will have deep expertise in Snowflake, DBT, Python, PySpark, Qlik Replicate, Astronomer Airflow, and CI/CD to develop scalable, secure, and high-performance data pipelines supporting modern analytics and business intelligence initiatives.

The successful candidate will play a key role in architecting data ingestion frameworks, implementing data governance and security, managing schema evolution, and optimizing cloud-based data platforms.

Key Responsibilities

  • Design, develop, and maintain scalable, resilient data pipelines using Snowflake features, including Snowpipe, Streams, Tasks, Dynamic Tables, and advanced SQL.
  • Build and maintain DBT models with testing, documentation, lineage, and reusable transformations.
  • Develop Python and PySpark-based ingestion frameworks for files, APIs, and enterprise data sources.
  • Build ingestion pipelines for structured and semi-structured data formats, including CSV, JSON, XML, Excel, fixed-width files, and multi-record layouts.
  • Design ingestion solutions for Mainframe VSAM/EBCDIC data sources.
  • Implement metadata-driven schema evolution and schema drift detection strategies.
  • Configure and manage Qlik Replicate for Change Data Capture (CDC) and database replication from Oracle, SQL Server, and DB2.
  • Develop robust, auditable, and recoverable data replication pipelines.
  • Implement Snowflake data governance using RBAC, masking policies, and security best practices.
  • Apply Protegrity (or similar tokenization platforms) for sensitive data protection.
  • Develop and orchestrate workflows using Astronomer Airflow with dependency management, scheduling, retries, and monitoring.
  • Integrate data pipelines with GitLab and Azure DevOps CI/CD pipelines.
  • Optimize Snowflake performance, compute resources, storage utilization, and query execution.
  • Implement monitoring, alerting, logging, and operational dashboards for data pipelines.
  • Collaborate with Data Architects, Analysts, Data Scientists, and business stakeholders to deliver reliable data solutions.

Required Skills

  • 8 12+ years of experience in Data Engineering.
  • Strong expertise in Snowflake architecture and development.
  • Hands-on experience with:
    • Snowpipe
    • Streams
    • Tasks
    • Dynamic Tables
    • Advanced SQL
    • Data Masking
    • RBAC
    • Performance Tuning
  • Strong experience with DBT (Data Build Tool).
  • Proficiency in Python and PySpark.
  • Experience with Qlik Replicate for CDC and database replication.
  • Hands-on experience with Astronomer Airflow workflow orchestration.
  • Experience implementing schema drift detection and schema evolution.
  • Knowledge of GitLab, Git workflows, and CI/CD automation.
  • Experience with REST APIs and enterprise data integration.
  • Strong understanding of data governance, metadata management, and data quality.
  • Excellent analytical, troubleshooting, and problem-solving skills.
  • Strong communication and collaboration skills.

Preferred Qualifications

  • Experience with Protegrity or similar data security/tokenization platforms.
  • Experience working with Oracle, SQL Server, and DB2 databases.
  • Knowledge of Azure DevOps and cloud-native data engineering practices.
  • Experience with enterprise-scale data lake and data warehouse implementations.
  • Exposure to Agile/Scrum development methodologies.

Experience Required

  • 8 12+ years of hands-on Data Engineering experience.

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