Senior Cloud Data Engineer – AWS, Python & ETL/ELT

**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.