> Markdown version of [/jobs/ext/4525582-data-engineer](https://www.wearedevelopers.com/jobs/ext/4525582-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Big Impact Tech (BIT) - **Location:** Washington, DC, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Information Systems, Databases, Continuous Integration, Data Dictionary, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Warehousing, DevOps, Apache Hive, NoSQL, Power BI, SQL Databases, Data Streaming, Tableau (Software), Unstructured Data, Google Cloud, Cloud Platform System, Data Ingestion, Azure Data Factory, Snowflake, Apache Spark, Git, Microsoft Fabric, Containerization, Data Lakes, Pyspark, Infrastructure Automation Frameworks, Information Technology, Deployment Automation, Qlikview, Data Management, Data Lakehouse, Azure Synapse Analytics, Data Pipelines, Databricks - **Published:** November 2, 2026 - **Apply:** https://www.juju.com/job/2_167801680 ## About the Role Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or a related field. 5+ years of experience in Data Engineering. 3+ years of hands-on experience with Databricks. Strong experience with PySpark, Spark SQL, and SQL. Experience building large-scale data pipelines and ETL/ELT solutions. Experience with cloud platforms such as Azure, AWS, or Google Cloud. Strong understanding of data modeling, data warehousing, and Lakehouse architectures. Experience working with relational and NoSQL databases. Preferred Qualifications Experience supporting Coast Guard or other government-related programs. Experience with Azure Databricks, Azure Data Factory, Microsoft Fabric, Synapse Analytics, or Snowflake. Knowledge of Delta Lake, Unity Catalog, and Databricks Workflows. Experience with real-time and streaming data solutions. Familiarity with DevOps practices, Git, CI/CD pipelines, and Infrastructure as Code. Experience with Power BI, Qlik, or Tableau reporting environments. xrbllit Relevant Databricks or cloud certifications preferred. Technical Skills Databricks PySpark Apache Spark Spark SQL SQL Delta Lake Data Lakehouse Architecture Azure Databricks Azure Data Factory Microsoft Fabric Snowflake Data Warehousing ETL/ELT Development Data Modeling Git CI/CD Cloud Platforms (Azure, AWS, GCP) ## Description We are seeking a skilled Data Engineer with strong Databricks expertise to support Coast Guard data modernization, analytics, and cloud transformation initiatives. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines, data lakehouse solutions, and cloud-based data platforms that enable efficient data integration, storage, processing, and analytics. The candidate will work closely with data architects, analysts, developers, and business stakeholders to deliver reliable, secure, and high-performing data solutions. Key Responsibilities Design, develop, and maintain scalable data pipelines using Databricks and cloud-native technologies. Build and optimize ETL/ELT processes for structured, semi-structured, and unstructured data. Develop and manage data ingestion frameworks from various source systems, APIs, databases, and files. Implement and maintain Delta Lake architecture and Lakehouse solutions. Develop PySpark, Spark SQL, and SQL-based transformations for large-scale data processing. Support data warehousing, data lakes, and enterprise analytics initiatives. Monitor and optimize data pipeline performance, reliability, and scalability. Ensure data quality, governance, lineage, and security across data platforms. Collaborate with business stakeholders and technical teams to understand requirements and deliver data solutions. Implement CI/CD practices and automated deployment processes for data engineering solutions. Troubleshoot and resolve production issues related to data ingestion, transformation, and reporting. Create and maintain technical documentation, data dictionaries, and architecture diagrams.