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Senior Data Engineer

Raas Infotek LLCDallas, TX🇺🇸United StatesPosted 11 Sept 2026

Why This Role Stands Out

This hybrid role offers a fantastic opportunity to leverage your 12+ years of expertise in designing and implementing scalable data solutions, working with cutting-edge cloud platforms and big data technologies. You'll thrive here if you are a seasoned data engineer passionate about building robust pipelines and contributing to enterprise-scale data platforms, and we encourage you to apply.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Dallas, TX, United States
Posted
21 hours ago
SQLAWSETLScrumSnowflakeAgileAirflowApacheApache SparkAzureBigQueryDatabricksGitGoogle CloudJenkinsKafkaPythonRedshiftTerraformdbt

Job Description

Senior Data Engineer

Experience: 12+ Years
Employment Type: W2

Job Description

We are looking for an experienced Senior Data Engineer with 12+ years of strong experience in designing, developing, and implementing scalable data engineering solutions. The ideal candidate will have extensive hands-on experience with cloud data platforms, ETL/ELT pipelines, data warehousing, big data technologies, and modern data architecture.

The candidate will be responsible for building reliable and high-performance data pipelines, integrating data from multiple sources, developing cloud-based data solutions, and supporting enterprise-scale data platforms. The role requires strong programming, analytical, problem-solving, and communication skills.

Key Responsibilities

  • Design, develop, and maintain scalable ETL/ELT data pipelines for large and complex datasets.
  • Develop high-performance data processing solutions using Python, SQL, PySpark, and Apache Spark.
  • Build and optimize data pipelines for both batch and real-time data processing.
  • Work with cloud platforms such as AWS, Azure, or Google Cloud Platform to develop and manage modern data solutions.
  • Design and implement data warehouses, data lakes, and lakehouse architectures.
  • Develop data solutions using technologies such as Snowflake, Databricks, Redshift, BigQuery, or equivalent platforms.
  • Implement data ingestion and transformation processes from databases, APIs, files, applications, and streaming sources.
  • Work with Apache Kafka or similar technologies for real-time/event-driven data processing.
  • Develop and manage workflows using Apache Airflow, AWS Glue, or other orchestration tools.
  • Perform data modeling, data profiling, data validation, and data quality checks.
  • Optimize SQL queries, Spark jobs, ETL processes, and data pipelines for performance and scalability.
  • Implement monitoring, logging, error handling, and troubleshooting mechanisms for production data pipelines.
  • Collaborate with Data Architects, Data Scientists, Business Analysts, Application Developers, and other stakeholders.
  • Participate in requirements gathering, technical design, development, testing, deployment, and production support.
  • Implement CI/CD practices for data engineering applications using Git, Jenkins, Azure DevOps, or similar tools.
  • Follow data governance, security, privacy, and compliance standards while working with enterprise data.
  • Troubleshoot production issues and provide root-cause analysis and permanent solutions.
  • Mentor junior and mid-level Data Engineers and provide technical guidance on best practices.

Required Technical Skills

  • 12+ years of experience in Data Engineering / Big Data / Data Platform development.
  • Strong programming experience in Python.
  • Advanced SQL skills with experience working on complex queries and large datasets.
  • Strong hands-on experience with PySpark / Apache Spark.
  • Extensive experience developing ETL/ELT pipelines.
  • Strong experience with at least one major cloud platform: AWS, Azure, or Google Cloud Platform.
  • Experience with modern data platforms such as Snowflake, Databricks, Redshift, or BigQuery.
  • Experience with data orchestration tools such as Airflow, AWS Glue, Azure Data Factory, or equivalent.
  • Experience with Kafka or other real-time streaming technologies is preferred.
  • Strong understanding of data warehousing, data lakes, data modeling, and dimensional modeling.
  • Experience with relational and NoSQL databases.
  • Strong understanding of distributed computing and large-scale data processing.
  • Experience with Git and CI/CD processes.

Preferred Skills

  • Snowflake and DBT
  • Databricks / Delta Lake
  • AWS Glue, S3, Lambda, Redshift
  • Azure Data Factory, ADLS, Synapse
  • Google Cloud Platform BigQuery, Dataflow, Pub/Sub
  • Apache Kafka / Kafka Streams
  • Terraform / Infrastructure as Code
  • Data governance and data quality frameworks
  • Real-time and streaming data pipelines
  • Experience with AI/ML data pipelines or GenAI data platforms
  • Experience working in Agile/Scrum environments

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field is preferred.

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