Role Description We are seeking a detail-oriented and organized Enrollment Clerk/Data Entry Specialist to support a Bureau of Indian Affairs (BIA) contract focused on records management and digitization. Remote work may be authorized based on security, workload, or operational need. Responsibilities - Front-line intake and application processing - Data entry and records maintenance - Customer and applicant support - Mail processing and front desk operations - Receive, log, and track all incoming CDIB applications and supporting documents - Review applications for completeness and accuracy based on BIA standards - Conduct genealogical research and documentation verification as needed - Prevent fraudulent submissions by validating authenticity of supporting evidence - Enter all applicant data into the Enrollment database, ensuring accuracy - Maintain both physical and electronic records - Prepare applicant correspondence including status updates, deficiency notices, and determinations - Staff analyze family tree history, verify lineage, check for fraud, and ensure eligibility Qualifications - Ability to collaborate with tribal representatives and federal staff - Proficiency in Microsoft Office Suite (Word, Excel, Outlook) - Strong attention to detail and organizational skills - Excellent communication and collaboration skills - High school diploma or equivalent; associate degree preferred - Minimum 2+ years of experience in data entry, records management, or administrative support - Experience in policy development and technical writing - Knowledge of Alaska Native communities, tribal enrollment, and genealogical research (preferred) Requirements - Limited in-state travel may be needed for training, outreach, or tribal coordination Benefits - Salary range: $40,083.00 to $48,020.00 annually - Competitive base salary commensurate with qualifications and experience - Comprehensive benefits package including medical, dental, and vision insurance - 401(k) plan with company matching - Tax-deferred savings options - Supplementary benefits - Paid time off - Professional development opportunities

Role Description A-TEK is seeking a Senior Data Engineer to support enterprise data modernization, cloud-native data engineering, analytics enablement, and data governance initiatives for Federal customers. This role focuses on designing and implementing scalable data platforms, automated ETL/ELT pipelines, and modern cloud-based data solutions supporting scientific, operational, and mission-critical environments. The ideal candidate combines strong hands-on engineering expertise with the ability to collaborate across technical and non-technical teams to modernize data ecosystems and improve enterprise data accessibility, quality, governance, and analytics capabilities. NOAA experience is preferred. This position is remote and requires the ability to obtain and retain a public-trust clearance. Responsibilities - Design, develop, and optimize enterprise data warehouses and large-scale ETL/ELT pipelines - Engineer cloud-native data processing solutions supporting structured, semi-structured, and unstructured data - Develop scalable ingestion and transformation frameworks for high-volume and real-time data processing - Support modernization of legacy data environments into cloud-based architectures - Design and implement data models, schemas, and database structures optimized for analytics and reporting - Develop metadata-driven automation, data quality validation, lineage tracking, and governance capabilities - Build and maintain reporting, analytics, and dashboarding solutions supporting operational and executive decision-making - Collaborate with architects, engineers, analysts, and business stakeholders to define technical requirements and implementation strategies - Support AI/ML and advanced analytics initiatives through scalable data engineering and MLOps-ready infrastructure - Implement Infrastructure-as-Code (IaC), CI/CD pipelines, and automated deployment processes - Perform database tuning, query optimization, and performance engineering activities - Support secure data management and compliance with Federal security and data governance requirements - Provide technical leadership, mentoring, and engineering best practices across project teams Qualifications - Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field - 7+ years of experience in data engineering, data warehousing, database engineering, or related disciplines - Strong experience designing and implementing ETL/ELT pipelines and enterprise data warehouse solutions - Experience with distributed processing frameworks and cloud-native data ecosystems - Strong experience with data modeling, database design, and dimensional modeling techniques - Experience implementing data governance, metadata management, data quality, and data integrity controls - Proficiency with SQL and Python-based data engineering and automation - Experience with cloud data platforms and services in AWS, Azure, or Google Cloud - Experience supporting large-scale, modern data modernization initiatives - Strong verbal and written communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders - Experience collaborating across cross-functional teams in Agile or DevSecOps environments Preferred Qualifications - NOAA or broader Federal civilian agency experience - Experience supporting scientific, environmental, geospatial, or research data environments - Experience with GIS or geospatial data platforms - Experience with AI/ML data engineering or MLOps support - Experience with Infrastructure-as-Code and CI/CD automation - Familiarity with metadata management, data catalogs, and enterprise governance frameworks - Experience with real-time streaming or event-driven data architectures - AWS or Azure certifications Preferred Technical Skills - SQL Server, PostgreSQL, Oracle, or cloud-native databases - Azure Data Factory, SSIS, Informatica, dbt, Airflow, or similar ETL frameworks - Azure Synapse, Databricks, Spark, Hadoop, Kafka, or distributed analytics platforms - Python, Pandas, NumPy, PySpark - Power BI, Tableau, SSRS, or enterprise analytics platforms - Docker, Kubernetes, Git, Azure DevOps, Jenkins, Terraform, or similar DevOps technologies - REST APIs and data integration services Compensation Salary Range: $160,000 – $170,000 annually (commensurate with experience, professional certifications and location) Benefits - Health, dental, and vision insurance - 401(k) with employer match - Paid time off - Professional development opportunities

• Support new and existing customers and their onboarding of IP data • Perform data mapping and manage complex datasets with high level of attention to detail • Migrate customers’ data into our preferred format • Coordinate and receive inputs needed from both customers and internal stakeholders • Maintain accurate customer records. • Resolve issues directly or bring in other internal resources to ensure all customer issues are resolved to the customer’s satisfaction in a timely and careful manner. • Stay current with system changes and updates. • Work closely with customer success, product, and other internal team leads to improve customer experience

• Define Data Platform Strategy: In partnership with senior leadership, define the vision, roadmap, and operating model for AssetWatch’s data platform, ensuring it supports analytics, product development, and AI initiatives across the organization. • Lead the Data Platforms Organization: Build, lead, and develop the data platforms team, establishing clear goals, accountability, and performance expectations. Develop managers and engineers while fostering a culture of ownership, collaboration, and continuous improvement. • Set Organizational OKRs: Partner with executive leadership to define strategic OKRs for the data platform organization and translate them into measurable goals for teams and individuals. • Own Data as a Company Asset: Establish the governance framework that ensures data across the organization is well-defined, trusted, and properly managed, including dataset ownership, data definitions, lineage, access controls, and lifecycle management. • Data Platform Architecture: Design and evolve AssetWatch’s cloud data platform using AWS technologies such as S3, Glue, Athena, Redshift, and Lambda to support scalable analytics, reporting, and AI workloads through MCPs. • Data Ingestion & Pipelines: Oversee the development and reliability of data pipelines ingesting information from product telemetry, APIs, and enterprise SaaS systems. • Curated Data & Data Modeling: Lead the creation of trusted datasets used for reporting, operational decision making, and machine learning. • AI-Ready Data Infrastructure: Ensure the company’s data platform is structured to support AI and machine learning initiatives by enabling reliable, well-modeled data inputs for ML pipelines and advanced analytics. • Enterprise Systems Data Integration: Partner closely with Enterprise Applications leadership to ensure systems such as Salesforce, finance platforms, and customer success tools integrate cleanly into the data platform. • Data Quality & Reliability: Establish monitoring and operational processes that ensure data accuracy, pipeline reliability, and data freshness. • Security, Privacy & Compliance: Work with IT and Security teams to ensure the data platform meets SOC2 and privacy requirements including access control, encryption, audit logging, and retention policies. • Operational Efficiency: Eliminate manual reporting workflows and redundant integrations by creating scalable, automated data pipelines and shared data models. • Cross-Functional Leadership: Lead highly visible initiatives that align teams across engineering, product, operations, and leadership to improve data reliability and organizational decision-making.