Role Description CORMAC is seeking a skilled Data Engineer to manage and optimize our data for powerful analytics and reporting. You will play a key role in building and maintaining scalable data processing pipelines while ensuring data integrity, security, and accessibility for business-critical applications. - Develop and maintain data processing applications using Apache Spark and Scala to process large-scale datasets efficiently. - Monitor and optimize database performance, including indexing, query optimization, and load balancing, to ensure high availability and low-latency data access. - Design and implement robust, scalable, and efficient database structures to support applications and data analytics. - Deploying and managing data infrastructure on AWS. - Assist in the migration of data between systems, including database upgrades, platform changes, and ETL processes for data integration. - Leveraging cloud-native services for data processing and storage. - Optimizing costs while maintaining performance and scalability. - Applying various transformations like data cleansing, aggregation, and enrichment. - Monitor data quality metrics and perform data cleansing as necessary. - Work with Product Owners and Business Analysts to refine user stories for data ingestion, processing, and reporting features. Qualifications - Bachelor’s in Computer Science, Computer Engineering, Information Systems, or related field. - 3+ years of experience as a Data Engineer or similar role. - 2+ years of experience working with Apache Spark, Scala, and Spark SQL. - Must have the ability to obtain a Public Trust (Tier 1) Security Clearance. - Experience with cloud platforms such as AWS, Google Cloud, or Azure, utilizing cloud services for data storage, processing, and retrieval. - Knowledge of data warehousing, data lakes, and cloud computing. - Familiarity with machine learning algorithms. - Knowledge of ETL processes and data modeling techniques. - Familiarity with ETL tools, REST APIs, and data integration techniques. - Understanding of data security and compliance best practices. - Ability to develop clear, efficient, scalable solutions for complex problems. - Understanding of data warehousing solutions and database architecture principles. - Effective communication and teamwork abilities. - Strong problem-solving skills and attention to detail. Requirements - Experience using Airflow, DBT, Postgres, Databricks, Amazon EMR & RDS. - Working experience on an Agile/Scrum or SAFe development team. Location Leesburg, VA Work Arrangement 100% Remote Benefits At CORMAC, we leverage the power of data management and analytics to enable our customers to achieve their strategic goals. With over 20 years of experience in health information technology (HIT), human-centered design principles, and Agile development methodologies, CORMAC delivers complex digital solutions to solve some of the most challenging problems facing public healthcare programs today. - As a US Federal Government contractor in the public healthcare sector, our work is impactful and cutting-edge while being performed in a supportive, collaborative, and welcoming environment. - We offer flexible work schedules with remote, hybrid, or fully in-person workplace options to empower our employees to decide the workplace most suitable for them. - At CORMAC, we have a highly diverse workforce and believe a work environment is a place where creativity, collaboration, enthusiasm, and innovation happen, regardless of location. Company Description US Citizenship Required/E-Verify Participation/EEO As an Equal Employment Opportunity employer, CORMAC provides equal employment opportunity to all employees and applicants without regard to an individual's protected status, including race/ethnicity, color, national origin, ancestry, religion, creed, age, gender, gender identity/expression, sexual orientation, marital status, parental status, including pregnancy, childbirth, or related conditions, disability, military service, veteran status, genetic information, or any other protected status.

The Data Steward is responsible for ensuring the quality, integrity, and appropriate use of data across the organization. This role plays a key part in supporting enterprise data governance initiatives by executing day-to-day stewardship activities, which may span master data, transactional data, and reference data. The Data Steward collaborates with both business and technical teams to ensure trusted and well-governed data assets are available for critical decision-making. DUTIES AND RESPONSIBILITIES · Review and validate enterprise data to ensure completeness, accuracy, and alignment with defined data standards. · Identify, investigate, and resolve data quality issues including duplicates, inconsistencies, and missing or invalid values. · Collaborate with business users and data analysts to refine data requirements and enforce data standards. · Participate in data quality reviews and assist with implementing corrective and preventative actions. · Manage stewardship workflows for data quality exceptions, including tasks related to matching, merging, or enrichment. · Support onboarding and validation of new data sources across transactional and reference systems. · Partner with data governance council to maintain and enforce policies related to data access, lineage, classification, and quality. · Document business metadata, data definitions, and stewardship procedures. · Assist with data profiling and root cause analysis across operational and analytical datasets. · Use tools such as Excel, SQL, and MDM or data quality platforms (e.g., Reltio) to monitor and manage data quality. · Provide support for data audits, regulatory reporting, or operational processes dependent on high-quality data. · Communicate with cross-functional stakeholders to resolve data issues and gather feedback. · Stay current on data governance and stewardship best practices, especially in regulated industries such as healthcare. · Perform other related duties as assigned by management. SUPERVISORY RESPONSIBILITIES - This job has no direct supervisory responsibilities.

• Design, build, and maintain scalable data pipelines for clients across industries • Architect and optimize cloud data warehouse solutions, adapting to each client's stack, which may include Snowflake, BigQuery, Redshift, Microsoft Fabric, or similar platforms • Lead data integration projects from source system to analytical layer, including scoping, delivery, and handoff • Work fluidly across a range of modern data tools and platforms as client engagements demand, picking up new technologies quickly and applying best practices regardless of the toolset • Collaborate with analysts and data scientists to ensure data is clean, reliable, and well-modeled • Champion data quality, testing, and observability best practices across client engagements • Produce and maintain clear technical documentation including pipeline architecture, data dictionaries, lineage maps, and runbooks so clients can understand and own their infrastructure long-term • Document engineering decisions, standards, and workflows in a way that supports knowledge transfer to both clients and junior team members • Research and evaluate new technologies and advocate for tooling investments that benefit the firm • Train and mentor junior team members on engineering standards, pipeline design, and best practices • Participate in client-facing communication, including requirements gathering and progress updates • Flex support when capacity allows: contribute to analyst-side deliverables such as Power BI dashboard development, ad-hoc reporting, or data visualization.

• Design data models and structures for analytics purposes • Design data ingestion and transformation pipelines • Design security model of data access, considering data privacy and compliance concerns • Lead tool selection with the focus on ingestion, data lake, data governance, data catalog • Ingest priority data into the data warehouse/data lake and prep the data for analysis