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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** HumCap, Inc. - **Location:** Plano, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Big Data, Cloud Computing, Cloud Database, Cloud Storage, Code Review, Information Systems, Computer Programming, Continuous Delivery, Continuous Integration, Data Validation, Information Engineering, Data Infrastructure, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Security, Data Systems, Data Warehousing, Relational Databases, Apache Hive, Python (Programming Language), Key Management, Meta-Data Management, Online Analytical Processing, Online Transaction Processing, Operational Databases, Performance Tuning, Cloud Services, Azure Machine Learning, SQL Databases, Data Streaming, Management of Software Versions, Azure Service Bus, Cloud Platform System, Data Ingestion, Azure Data Factory, Apache Spark, Data Layers, Data Lakes, Pyspark, Information Technology, Apache Kafka, Machine Learning Operations, Data Lakehouse, Terraform, Data Pipelines, Databricks - **Published:** October 23, 2026 - **Apply:** https://www.thejobnetwork.com/job/7c779b69-f5dc-44ae-91d0-a46bff83b2fa/senior-data-engineer ## About the Role * 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., * 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 Authorization: Candidates must be authorized to work in the United States. Sponsorship is not available for this position. ## Description Job DescriptionSenior Data Engineer - Plano, TX | Full-Time / HybridPosition Overview We 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.