Senior Data Engineer

HumCap

  • Plano, TX
  • 1 day ago

    Highlights

    Cloud Data Platform Integrate Databricks with Azure cloud services, including cloud data lakes, data integration services, event-streaming platforms, data warehouses, secrets management, and CI/CD tooling. The ideal candidate will have experience working in high-volume data environments and collaborating with data architects, data scientists, business stakeholders, and cloud infrastructure teams to deliver reliable, secure, and high-performance data solutions.

    Numbers & Facts

    LocationPlano, TX

    Description

    Senior Data Engineer –Plano, TX | Full-Time / HybridPosition OverviewWe are seeking a highly skilled and experienced Senior Data Engineer to help design, develop, and optimize a modern cloud-based data platform.This role will focus heavily on Azure Databricks, PySpark, Spark SQL, scalable ETL/ELT pipelines, and data lakehouse architecture. The ideal candidate will have experience working in high-volume data environments and collaborating with data architects, data scientists, business stakeholders, and cloud infrastructure teams to deliver reliable, secure, and high-performance data solutions.Key ResponsibilitiesData Architecture & Engineering
    • Design and implement scalable ETL/ELT pipelines using Azure Databricks, PySpark, and Spark SQL.
    • Build robust data ingestion workflows from diverse sources, including APIs, event-streaming platforms, relational databases, and cloud storage.
    • Develop and maintain Bronze, Silver, and Gold data layers using a modern medallion architecture.
    • Establish best practices for Delta Lake, schema evolution, data versioning, and governance.
    • Optimize large-scale data pipelines for performance, reliability, and cost efficiency through partitioning, caching, clustering, and Spark configuration tuning.
    Cloud Data Platform
    • Integrate Databricks with Azure cloud services, including cloud data lakes, data integration services, event-streaming platforms, data warehouses, secrets management, and CI/CD tooling.
    • Implement secure and governed access to enterprise data using managed identities, role-based access controls, and data protection techniques.
    • Support the development and evolution of a scalable cloud-native data platform.
    Collaboration & Technical Leadership
    • Partner with data analysts, data scientists, business stakeholders, and other technical teams to understand data requirements.
    • Build trusted datasets, reporting structures, and business-critical KPIs.
    • Provide technical leadership and mentorship to junior and mid-level engineers.
    • Conduct code reviews and contribute to architectural and engineering standards.
    • Collaborate with architecture, security, and infrastructure teams to ensure data solutions meet organizational security and compliance requirements.
    Data Quality & Monitoring
    • Implement data quality checks, validation frameworks, alerts, and lineage tracking.
    • Develop monitoring and observability solutions for mission-critical data pipelines.
    • Establish automated failure detection, alerting, and recovery processes.
    • Continuously improve data reliability, scalability, and operational performance.
    Required Qualifications
    • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field.
    • 5+ years of professional data engineering experience, including 3+ years working extensively with Azure Databricks and Apache Spark.
    • Strong expertise with Delta Lake, Unity Catalog, Databricks Notebooks, and SQL-based data warehousing.
    • Hands-on experience with Azure data services and cloud infrastructure.
    • Strong programming skills in Python and SQL;familiarity with Scala is a plus.
    • Solid understanding of data modeling, including OLTP/OLAP environments and star/snowflake schemas.
    • Experience with performance optimization and tuning of large-scale data workloads.
    • Experience implementing CI/CD for data engineering environments using tools such as Azure DevOps, Terraform, or Databricks CLI.
    • Strong understanding of data security, governance, and access-control practices.
    Preferred Qualifications
    • Databricks certification or comparable professional certification.
    • Experience building real-time or streaming data pipelines using technologies such as Structured Streaming, Event Hubs, or Kafka.
    • Experience supporting machine learning workflows or ML platforms.
    • Familiarity with business intelligence and visualization platforms.
    • Experience with data cataloging, lineage, and enterprise governance tools.
    • Knowledge of data privacy, security, and compliance frameworks.
    • Experience working in high-volume, production data environments.
    Work Arrangement
    • Location: Plano, TX
    • Schedule: Full-Time
    • Work Arrangement: Hybrid — 4 days per week on-site
    • Remote: 1 day per week
    • Relocation Assistance: Not Provided
    • Work Authorization: Candidates must be authorized to work in the United States. Sponsorship is not available for this position.
    • Local Requirement: Candidates must be able to commute to the Plano/Dallas–Fort Worth area and work on-site four days per week.
    Compensation & BenefitsThe organization offers competitive compensation and a comprehensive benefits package. Additional details regarding compensation and benefits will be discussed during the interview process.

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