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Senior Data Engineer

  • North Carolina, Charlotte

  • 06/26/2026

  • Contract

  • Active

Job Description:

  • Job Summary
    The Senior Data Engineer will design, develop, and optimize scalable cloud-based data platforms that support enterprise analytics, regulatory reporting, business intelligence, and machine learning initiatives. This role is responsible for building high-performance ETL/ELT pipelines, implementing data engineering best practices, and delivering reliable, high-quality datasets across cloud environments. The ideal candidate will have strong expertise in Python, SQL, cloud data platforms, distributed data processing, and modern data engineering technologies.

    Key Responsibilities
    • Design, develop, and maintain scalable ETL/ELT pipelines to ingest data from multiple internal and external sources.
    • Build and optimize cloud-based data pipelines using modern data engineering frameworks and orchestration tools.
    • Develop data transformation workflows for structured, semi-structured, and unstructured data.
    • Design, develop, and maintain data models supporting analytics, reporting, and machine learning initiatives.
    • Collaborate with data architects, business analysts, data scientists, and cross-functional teams to deliver high-quality data solutions.
    • Implement data quality validation, metadata management, and data governance standards.
    • Optimize SQL queries and distributed processing jobs for performance and scalability.
    • Develop reusable data engineering frameworks, automation scripts, and best practices.
    • Support batch and near real-time data processing requirements.
    • Monitor production data pipelines, troubleshoot failures, and participate in production support and on-call rotations.
    • Participate in Agile ceremonies, architecture discussions, code reviews, and technical design sessions.
    • Ensure compliance with enterprise security, privacy, and regulatory standards.
    • Create and maintain technical documentation for data pipelines, processes, and architecture.

    Required Qualifications
    • Bachelor's degree in Computer Science, Information Systems, or a related field.
    • 6+ years of experience in Data Engineering or ETL development.
    • Strong SQL skills with experience designing, optimizing, and troubleshooting complex queries.
    • Hands-on experience with Python for data processing, automation, and pipeline development.
    • Experience with cloud platforms such as AWS, Azure, or GCP.
    • Experience with ETL tools such as Informatica, Talend, DataStage, AWS Glue, Azure Data Factory, or similar technologies.
    • Experience working with analytical databases such as Snowflake, Amazon Redshift, Azure Synapse, BigQuery, or equivalent.
    • Experience with Apache Spark or PySpark for distributed data processing.
    • Experience using Git and CI/CD practices for source control and deployment automation.
    • Strong understanding of data warehousing concepts, dimensional modeling, and data architecture.
    • Strong analytical, troubleshooting, and problem-solving skills.
    • Excellent communication and collaboration skills.

    Preferred Qualifications
    • Experience with Apache Airflow, Control-M, or other workflow orchestration platforms.
    • Experience with Kafka or other streaming technologies.
    • Experience with Databricks and Delta Lake.
    • Experience working in financial services, banking, insurance, risk management, or related industries.
    • Familiarity with data governance, data lineage, and metadata management tools.
    • Experience supporting machine learning or AI data pipelines.
    • Experience working in Agile/Scrum development environments.

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