• 5+ years working on the role professionally. • Coding Python and use in data processing solutions and related data technologies like Pandas, and PySpark. • Consume data from different sources like REST APIs. • Work with relational and non-relational data stores (like: HBASE, Cassandra or MongoDB; S3, blobs). • Consumption; Design. • Data Streams (Kafka, Kinesis, Flume,) and message queuing (SQS, SNS, RabbitMQ, etc). • Ensure that the data model scales and enables high performance. • Distributed data stores. • Data/Stream processing (Spark, Flink, Hadoop). • Data pipelines, data ingestion pipelines, scalable streaming data pipelines processing. • ETL using solutions: Talend; Informatica; SQL Server Integration Services (SSIS). • Data warehouse (Snowflake, Redshift, Hive). • Implementation of data warehouse solutions, providing near real-time data to a variety of client systems; Using SQL databases to construct data storage. • Reporting / BI, design, implementation, and enhancement of BI tool is a plus. Looker; Power BI; Tableau. • Experience designing and implementing data applications and services on the public cloud, AWS, GCP, or Azure using PaaS platforms. • Familiarity with data privacy regulations and best practices.

• Hands-on development and optimization of the data backend, ensuring stability, performance, and architectural consistency • Build and optimize Snowflake data models and workloads (raw → curated → data products), with strong focus on performance and cost efficiency • Develop and maintain transformation logic in dbt (modeling, refactoring, tests, documentation, macros) to ensure data quality and scalability • Orchestrate reliable data pipelines using Airflow/Astronomer (DAG design, dependencies, retries, monitoring/alerting) for production readiness • Use Git + CI/CD to enforce code quality and enable automated testing and deployments across the data platform • Work with IT and business colleagues to develop solutions to specific problems that at times leverage existing solutions and systems • Build professional relationships with clients, management, and team members to ensure the delivery of proposed solutions

The Role We're looking for a product-minded Senior Data Engineer to lead the buildout of a new, greenfield enterprise data platform at Fusion. This is not a maintenance role. You will architect and own a new data platform product from the ground up-designing the infrastructure, pipelines, storage layers, and connectors that unify resilience data across customers, systems, and cloud environments. You will define how data is ingested, modeled, stored, governed, and exposed across Fusion's ecosystem. This platform will power next-generation analytics, intelligent functionality, integrations, and external data products. This is a high-ownership opportunity for someone who wants to build something foundational, influence architectural direction, and create a scalable data platform that becomes core to Fusion's long-term strategy. Key Responsibilities • Architect and build Fusion's next-generation enterprise data platform from the ground up, including data lake and warehouse components.• Design and implement scalable ETL/ELT pipelines to ingest and transform data from internal systems, customer environments, and third-party platforms.• Develop and/or leverage reusable ingestion frameworks and system connectors (e.g., Salesforce, ServiceNow, APIs, cloud storage, event streams).• Define data modeling standards, transformation layers, and storage strategies to support analytics, reporting, and product capabilities.• Establish best practices for data governance, quality, observability, lineage, and security across the platform.• Build backend services and APIs that expose data capabilities to downstream applications and products.• Partner with product and engineering leadership to shape the long-term data platform roadmap. Knowledge, Skills, and Abilities • Strong SQL expertise with experience designing performant data models and production-grade transformations.• Experience building data lakes, warehouses, and distributed data systems from the ground up.• Experience with one or more modern data platform technologies such as Snowflake, Databricks, AWS, Azure, or GCP.• Strong understanding of ETL/ELT patterns, orchestration, and pipeline reliability.• Experience designing and implementing enterprise system integrations and APIs.• Strong engineering fundamentals with focus on scalability, performance, monitoring, and security.• Experience with Salesforce or ServiceNow data models and integrations (bonus).• Strong Java skills or experience building backend services in Java (bonus).• Experience working in Azure environments (bonus).• Product-oriented mindset with the ability to make pragmatic architectural decisions in ambiguous, early-stage environments. Qualifications (Education and Experience) • Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.• 5+ years of experience in data engineering, backend data systems, or platform engineering roles.• Experience building or significantly expanding a data platform or data infrastructure in a production environment.• Experience working in cloud-native environments.• Experience designing enterprise-grade integrations and connectors.• Experience with Salesforce or ServiceNow integrations (nice to have).• Experience with Java-based services (nice to have).• Experience with Azure (nice to have). Milestones for the First Six Months In one month, you will: - Complete onboarding and gain deep familiarity with Fusion's products, architecture, and long-term platform vision - Assess the current state of data infrastructure and define a proposed architecture for the new platform - Align with product and engineering leadership on platform scope and priorities In three months, you will: - Deliver the first foundational components of the greenfield data platform (core storage layer, initial pipelines, and architecture patterns) - Implement initial ETL/ELT workflows and at least one production-grade system connector - Establish standards for modeling, governance, and observability In six months, you will: - Own and deliver the first production-ready version of Fusion's new data platform product - Have multiple ingestion pipelines and connectors operating reliably in production - Serve as the architectural owner of the platform, driving roadmap and technical direction - Propose and lead the next phase of platform expansion (scalability, performance optimization, advanced integrations) Compensation & Benefits The annual base salary range for this position is $135,000-$155,000, depending on the candidate's experience, qualifications, and relevant skill set. The position is also eligible for an annual bonus. Fusion offers a comprehensive benefits package including medical, dental, vision, and a 401(k) plan. Disclaimers Fusion is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, age, pregnancy, military service or discharge status, genetic information, sex, sexual orientation, gender identity, or national origin. Nothing in this job posting should be construed as an offer or guarantee of employment.

Analytica is seeking a Senior Data Architect to design, implement, and optimize enterprise data solutions in support of federal government missions. The Data Architect will play a hands-on role in modernizing data environments, leveraging cloud-native technologies, Databricks, and advanced data engineering frameworks to ensure scalable, secure, and high-performing solutions. This role requires strong expertise in cloud platforms (AWS, Azure, GCP), big data ecosystems, and modern data architecture patterns, along with an ability to translate mission needs into technical solutions. 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. The company offers competitive compensation with opportunities for bonuses, employer-paid health care, training and development funds, and 401k match.    Responsibilities include (but not limited to):  - Design and implement scalable data architectures for structured, semi-structured, and unstructured data. - Lead the modernization of legacy data environments into cloud-based, big data platforms. - Architect solutions leveraging Databricks, Spark, Delta Lake, and related big data technologies. - Define and enforce data governance, data security, and metadata management practices in compliance with federal standards. - Collaborate with government stakeholders, program managers, and development teams to ensure alignment with mission objectives. - Develop data models, pipelines, APIs, and integration strategies across multiple data sources and platforms. - Ensure architectures support analytics, AI/ML, and business intelligence use cases. - Mentor data engineers and developers, promoting best practices in coding, design, and performance optimization. - Support capture and proposal activities by shaping technical solutions and writing architecture content for bids.  Basic Qualifications:  - Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field (Master’s preferred). - 8+ years of experience in data architecture, data engineering, or solution architecture, including at least 3 years with cloud-based solutions. - Databricks certification (such as Databricks Certified Data Engineer Associate or Professional) - Expertise in Databricks, Apache Spark, Delta Lake, and distributed data processing frameworks. - Strong knowledge of AWS (Glue, S3, Redshift, EMR), Azure (Synapse, Data Lake, Purview), or GCP (BigQuery, Dataflow, Dataproc). - Experience designing data lakes, data warehouses, and streaming/real-time data architectures. - Familiarity with federal data standards (e.g., FISMA, FedRAMP, CUI handling, data governance frameworks). - Proficiency in SQL, Python, and big data query optimization. - Must be US Citizen - Must be able to obtain and maintain a Public Trust security clearance - Preferred: - Certifications in cloud platforms (AWS Certified Data Analytics, Azure Data Engineer, GCP Data Engineer). - Experience supporting federal data modernization, digital transformation, or analytics programs. - Familiarity with data governance tools (Collibra, Alation, Informatica, Purview). - Exposure to AI/ML pipelines and MLOps in cloud environments About ANALYTICA: Analytica is a leading consulting and information technology solutions provider to public sector organizations supporting health, civilian, and national security missions. Founded in 2009 and headquartered in Bethesda, MD, the company is an established SBA small business that has been recognized by Inc. Magazine each of the past three years as one of the 250 fastest-growing companies in the U.S.  Analytica specializes in providing software and systems engineering, information management, analytics & visualization, agile project management, and management consulting services. The company is appraised by the Software Engineering Institute (SEI) at CMMI® Maturity Level 3 and is an ISO 9001:2008 certified provider. Analytica LLC is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all individuals, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other characteristic protected by applicable federal, state, or local law. As a federal contractor, we comply with the Vietnam Era Veterans' Readjustment Assistance Act (VEVRAA) and take affirmative action to employ and advance in employment qualified protected veterans. We ensure that all employment decisions are based on merit, qualifications, and business needs. We prohibit discrimination and harassment of any kind. Analytica LLC also provides reasonable accommodations to applicants and employees with disabilities, in accordance with applicable law. To enhance efficiency, fairness, and accuracy, Analytica may use AI-assisted tools to support certain aspects of our hiring process. - Application Review: AI tools may help identify skills and experiences relevant to the role. - Interview Support: AI-powered notetaking tools may be used during interviews to document discussions and summarize key points. These tools are used to assist our team. All hiring decisions are made by Analytica recruiters and hiring managers. By submitting an application, you acknowledge that AI-assisted tools may be used to support parts of the application and interview process. When receiving email communication from Analytica, please ensure that the email domain is analytica.net to verify its authenticity.