• Design and implement scalable and reliable data warehouse architecture, including data models, storage strategies, and processing layers. • Develop and maintain a robust role-based access control (RBAC) model to ensure secure and appropriate access to data across the organization. • Design, implement, and maintain inbound and outbound data pipelines, ensuring reliability, observability, and data integrity. • Optimize SQL queries, data models, and compute/storage resource usage to ensure cost-efficiency and high performance of the data platform. • Implement and enforce data protection and security best practices, including handling of sensitive and regulated data. • Work closely with analytics and business teams to understand their needs and deliver efficient, scalable, and reliable data solutions. • Improve and automate data governance practices, including data quality controls, metadata management, lineage, and compliance-related processes. • Monitor and troubleshoot data pipelines and platform issues, ensuring stability and timely resolution of incidents. • Continuously improve the data platform architecture, tooling, and development practices.

• Own design and maintenance of all aspects of data solutions including modeling, developing, technical documentation, data diagrams and data dictionaries. • Provide expertise in the development of standards, architectural governance, design patterns, and practices, evaluate best applicable solutions for different use cases • Determines and develops architectural approaches and solutions, conducts business reviews, documents current systems, and develops recommendations • Lead the data strategy and own the vision and roadmap of data products • Work with stakeholders to ensure that data related business requirements for protecting sensitive data are clearly defined, communicated, and well understood and considered as part of operational prioritization and planning • Develop, maintain, and optimize data infrastructure using Delta Lake, MLflow, and Databricks SQL to enhance data management, processing, and analytics. • Utilize Snowflake’s features such as data sharing, zero-copy cloning, and automatic scaling to optimize data storage, accessibility, and performance. • Ensure effective management of both semi-structured and structured data within Snowflake’s architecture. • Implement and manage data storage solutions using Amazon S3, perform data warehousing with Amazon Redshift. • Design and implement data integration workflows using AWS Glue to orchestrate and automate data movement and transformation. • Design and implement scalable data pipelines using tools like Apache Kafka or Apache Airflow to facilitate real-time data processing and batch data workflows. • Apply advanced analytics techniques, including predictive modeling and data mining, to uncover insights and drive data-driven decision-making.

Role Description Analytica is seeking a mid-level Data Engineer (Azure) to design, build, and maintain secure, scalable, cloud-based data solutions supporting federal data programs. This role is hands-on and delivery-focused, working within established Azure architectures to develop reliable data pipelines, analytics-ready datasets, and reporting solutions in regulated environments. The Data Engineer will collaborate closely with senior engineers, architects, analysts, and government stakeholders to implement well-defined data requirements and support analytics, dashboards, and operational reporting. Key Responsibilities - Build, maintain, and optimize Azure-based data pipelines and workflows using Azure Data Factory, ADLS Gen2, Synapse Analytics, Azure SQL, Python, and SQL. - Support batch and near–real-time data ingestion, transformation, enrichment, and aggregation to deliver analytics- and reporting-ready datasets. - Implement data quality checks, schema management, and validation to ensure reliable, trusted, and well-documented data. - Develop and maintain analytical data models (e.g., star and snowflake schemas) to support dashboards, reporting, and operational insights. - Contribute to CI/CD pipelines, monitoring, troubleshooting, and performance tuning to ensure reliable data operations. - Implement security controls, access management, and data governance practices aligned with federal compliance requirements. - Work within Agile teams, collaborating closely with senior engineers, analysts, and stakeholders to deliver well-defined data requirements. Qualifications - U.S. citizenship with the ability to obtain a U.S. Federal security clearance. - Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent professional experience). - 3+ years developing and deploying Azure data pipelines for use in machine learning models or supporting data pipelines for such models. - Proficiency in Python for data engineering tasks (Pandas required). Benefits - Competitive compensation with opportunities for bonuses. - Employer-paid health care. - Training and development funds. - 401k match. Company Description Analytica has been recognized by Inc. Magazine as one of the fastest-growing 250 businesses in the US for 3 years. We work with U.S. government clients in health, civilian, and national security missions to build better technology products that impact our day-to-day lives.

• Design scalable, low-latency, and highly reliable data systems • Own the architectural vision for the Market Data Lakehouse • Collaborate closely with teams to enable fast experimentation • Drive performance optimization and long-term scalability • Document architectural decisions and maintain technical roadmaps