Senior Data Engineer with Security Clearance

TIAG is now hiring a Senior Data Engineer to join our team supporting the Federal Emergency Management Agency (FEMA). This position is expected to report onsite in Washington DC in a hybrid capacity. A government issued security clearance must be processed to start work, so US Citizenship is a requirement for consideration. To address FEMA's data and analytics gaps, the Office of Policy and Program Analysis (OPPA) established the Enterprise Data and Analytics Modernization Initiative (EDAMI) Program to create an enterprise analytics capability by making improvements in people, process, and technology. This role must have the ability to work at FEMA HQ in Washington DC as needed. The Senior Data Engineer will be a key technical leader in supporting TIAG's growing team in the Washington DC Metro area. The Senior Data Engineer is responsible for coordinating, communicating, and executing to provide comprehensive data migration, engineering solutions, and source system integration support to deliver mission needs through a focused effort on creating a strong cadre of subject matter experts, streamlined and re-engineered business processes, and development and delivery of a new IT system supporting a greater enterprise data analytics business capability. The ideal candidate for this position will possess a wide range of data engineering skills including technical, analytical, and communication skills that can support FEMA in its effort to develop, design, and implement innovative data strategies and solutions. The candidate must possess a strong understanding of data integration work, including developing a data model, maintaining a data warehouse and analytics environment, and writing scripts for data integration and analysis. In this position, you will work with data (raw, structured, unstructured) to identify opportunities to make improvements, identify correlations, patterns or trends that support data driven decision making. Responsibilities: Collaborate with other engineers on the design, development, and maintenance of highly scalable and efficient data pipelines using PySpark and Databricks for batch and potentially streaming data processing. Establish and enforce data quality standards, implement monitoring, and develop processes to ensure data accuracy and consistency across all data assets. Drive initiatives to improve data pipeline reliability, scalability, and cost-effectiveness. Collaborate closely with data scientists, data analysts, data stewards, and business stakeholders to understand data requirements and translate them into technical solutions. Provide technical leadership, guidance, and mentorship to fellow data engineers, fostering a culture of technical excellence and continuous learning. Evaluate and recommend new data engineering technologies, tools, and methodologies to improve our data platform capabilities and efficiency. Proactively identify, troubleshoot, and resolve complex data-related issues, performance bottlenecks, and system failures. Automate data processes, infrastructure provisioning, and deployment workflows using DevOps principles and CI/CD pipelines. Contribute significantly to the strategic planning, design, and architecture of our evolving data platforms and infrastructure. Develop, maintain, and optimize complex data models and ETL/ELT processes to ensure data integrity, performance, and accessibility. Required Experience: Proven experience designing and implementing data solutions on at least one major cloud-based data platform (e.g., AWS, Azure, GCP), utilizing relevant services (e.g., S3, ADLS, BigQuery, Redshift, Snowflake). Strong knowledge of database systems, including relational databases (e.g., SQL Server, Oracle, Postgres) and experience with schema design, query optimization, and performance tuning. Experience with data replication techniques such as Change Data Capture (CDC) and other data synchronization strategies is essential. Deep expertise and strong proficiency in Python and PySpark for data manipulation, transformation, and analysis. Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field, or equivalent practical experience. 5+ years of progressive experience in data engineering, with a strong track record of building and optimizing large-scale data pipelines in a production environment. Extensive hands-on experience with Databricks and/or advanced knowledge of Apache Spark internals and optimization techniques. Solid understanding of data warehousing concepts, dimensional modeling, data lake architectures, and data mesh principles. Understanding of object-oriented programming principles, design patterns, and software development best practices. Experience integrating with various APIs, including understanding different authentication methods (e.g., OAuth, API keys), handling rate limiting, and implementing pagination strategies to extract data. Experience integration testing and unit testing with Python. Experience with DevOps practices, including CI/CD pipelines (e.g., Jenkins, GitLab CI, Azure DevOps), infrastructure as code (e.g., Terraform, CloudFormation), and monitoring/logging tools. Excellent analytical, problem-solving, and debugging skills with the ability to tackle complex technical challenges independently. Strong communication, collaboration, and interpersonal skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences. Experience working effectively in an Agile development environment (Scrum, Kanban, SAFe Agile is a plus). Position requires an active Public Trust at minimum to be considered. Preferred Qualifications: Experience with data streaming technologies (e.g., Kafka, Kinesis, Spark Streaming, Flink). Familiarity with data catalog, data lineage, or data governance tools (Open Metadata). Experience with data visualization tools (e.g., Tableau and Power BI) from a data provisioning perspective, including creating reports for internal team use such as pipeline monitoring, access control reporting, and other operational metrics. Experience with a wide range of database technologies is a significant plus, demonstrating adaptability and broad technical knowledge. TIAG is a federal contractor and an equal opportunity and affirmative action employer that does not discriminate and employment decisions shall be based solely on merit and without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. This policy applies to all terms and conditions of employment. To achieve our goal of equal opportunity, TIAG maintains an affirmative action plan through which it makes good faith efforts to recruit, hire, and advance in employment qualified individuals with disabilities and protected veterans. Pay Range: $100,000 - $140,000 per year