**FULLY REMOTE**
ScolerTec Inc. has multiple openings for Senior Cloud Data Engineer to support a large-scale federal cloud modernization program.
The Senior Cloud Data Engineer will design, build, test, and maintain scalable cloud-based data engineering solutions supporting analytics, reporting, data modernization, and operational decision-making. The role includes developing secure and performant data pipelines, ETL/ELT processes, data transformations, system integrations, data marts, and cloud data platform services.
The ideal candidate will have strong hands-on experience with AWS, SQL, Python, ETL/ELT, enterprise-scale data pipelines, cloud data platforms, data modeling, and batch/near-real-time data integration.
Key Responsibilities
- Design and develop scalable, secure cloud-based data platforms supporting operational data, reporting, and analytics.
- Build and maintain data ingestion and ETL/ELT pipelines integrating data from multiple enterprise sources.
- Develop transformation logic supporting both near-real-time and batch processing.
- Design and maintain downstream data marts, gold layers, and reusable data services.
- Implement logical, physical, and dimensional data models.
- Work with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or similar technologies.
- Develop high-quality, testable code using SQL, Python, and secure coding practices.
- Integrate pipelines with cloud messaging, compute, and storage services.
- Implement data-quality checks, validations, monitoring, and error-handling mechanisms.
- Optimize data pipelines for performance, scalability, reliability, and cost.
- Support CI/CD-enabled data deployments, automated testing, and promotion across environments.
- Develop and maintain technical documentation including source-to-target mappings, data models, design documents, testing documentation, runbooks, and workflows.
- Support metadata, data classification, governance, and audit requirements.
- Partner with Data Architecture, Data Governance, Migration, DBA, QA, and application teams.
- Support data migration, archival, disaster recovery, and failover-testing initiatives.
Qualifications
- MA/MS with 5+ years or BA/BS with 7+ years of relevant experience, or equivalent experience as defined by the program.
- Strong professional experience in data engineering and enterprise data platforms.
- Hands-on experience building enterprise-scale data pipelines.
- Strong proficiency with SQL and Python.
- Strong experience with ETL/ELT frameworks and data transformation.
- Experience with AWS data and compute services.
- Experience developing solutions on cloud-based data platforms.
- Experience with data orchestration tools.
- Experience with cloud messaging and storage technologies.
- Experience with streaming or near-real-time data ingestion.
- Experience with data modeling and data architecture.
- Familiarity with data governance, metadata, and classification standards.
- Experience working in Agile/Scrum environments.
- Experience in regulated or compliance-driven environments.
- Ability to mentor junior data engineers.
Must Have
- AWS
- Data Engineering
- SQL
- Python
- ETL / ELT
- Enterprise data pipelines
- Cloud data platforms
- Data modeling
- Data orchestration
- Batch and near-real-time processing
- Data quality and validation
- CI/CD
Nice to Have
- Snowflake
- Databricks
- AWS Redshift
- Data lake / lakehouse architecture
- Streaming technologies
- Metadata management
- Data governance
- Data classification
- Data migration
- Disaster recovery
- Infrastructure as Code
- Federal or regulated-environment experience
Preferred Certifications
- AWS Certified Data Engineer
- AWS Certified Solutions Architect – Professional
- AWS Certified Data Analytics – Specialty
- Snowflake SnowPro Core
- Databricks Certified Data Professional
- Certified Data Management Professional (CDMP)
- Other relevant cloud-platform certifications.
Communication & Organizational Skills
- Excellent written and verbal communication skills.
- Strong analytical and problem-solving abilities.
- Ability to collaborate with architects, DBAs, analysts, QA teams, and customer stakeholders.
- Ability to work independently and across multiple Agile teams.
- Strong documentation and customer-facing skills.
