Data Engineer

Job Title: Data Engineer

Location: Dallas, TX / Plano, TX (Onsite)

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Job Summary

We are seeking a Data Engineer with strong experience in designing, building, and maintaining scalable data pipelines and ETL frameworks. The ideal candidate has a solid background in data modeling, SQL, Python, and cloud data platforms (Azure, AWS, or GCP), and works well in Agile environments to deliver data solutions supporting analytics, BI, and machine learning initiatives.

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Key Responsibilities

• Design, develop, and maintain data pipelines and ETL processes to support analytics and business applications.

• Build and optimize data models, ensuring efficient data flow and transformation.

• Develop and maintain scalable data warehouses / data lakes using cloud platforms (Azure, AWS, or GCP).

• Collaborate with data analysts, data scientists, and business teams to understand requirements and translate them into technical solutions.

• Implement data validation, quality checks, and governance standards.

• Monitor, troubleshoot, and optimize data systems for performance and scalability.

• Integrate data from multiple sources including APIs, flat files, databases, and third-party systems.

• Ensure data security, integrity, and compliance with corporate standards.

• Work closely with DevOps teams to automate deployments using CI/CD tools.

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Required Skills

• 5–8 years of experience as a Data Engineer or ETL Developer.

• Strong experience with SQL, Python, and data transformation logic.

• Proficiency with ETL tools (ADF, Informatica, Talend, or Apache Airflow).

• Experience with cloud platforms — preferably Azure Data Factory, Azure Synapse, Databricks, or AWS Glue / Redshift.

• Solid understanding of data warehousing concepts (Kimball, star schema, SCD).

• Hands-on with big data frameworks (Spark, Hadoop) and NoSQL databases (MongoDB, Cassandra).

• Familiarity with version control (Git) and CI/CD pipelines (Azure DevOps, Jenkins).

• Strong analytical, communication, and problem-solving skills.

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Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.

• Experience with containerization (Docker, Kubernetes) and Infrastructure as Code (Terraform).

• Exposure to streaming data platforms such as Kafka or Kinesis.

• Experience working in Agile/Scrum environments.

• Certification in Azure Data Engineer Associate, AWS Data Analytics, or GCP Professional Data Engineer is a plus.

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Soft Skills

• Strong attention to detail and documentation.

• Effective communication with technical and business stakeholders.

• Ability to manage multiple priorities in a fast-paced environment.

• Team player with a proactive and collaborative attitude.