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

ScolerTec Inc; United States; On-site; USD 130,000 - 170,000; Full time

Job summary

ScolerTec Inc. is hiring a Senior Cloud Data Engineer to design, build, test, and maintain scalable cloud-based data pipelines and platforms supporting analytics and decision-making.

You will implement secure, performant ETL/ELT processes, data transformations, and data marts using Snowflake, Databricks, and AWS Redshift, with strong SQL and Python coding practices.

Qualifications

• 5+ years in data engineering or equivalent experience.
• Strong hands-on experience with enterprise-scale data platforms.
• Proficient in SQL and Python.
• Experience with ETL/ELT and data transformations.
• Experience with AWS data and compute services.
• Experience with data orchestration tools.
• Experience with near-real-time and batch processing.
• Ability to mentor junior data engineers.

Responsibilities

• Design and develop scalable cloud-based data platforms.
• Build and maintain data ingestion and ETL/ELT pipelines.
• Develop transformation logic for near-real-time and batch processing.
• Design and maintain data marts and reusable data services.
• Implement data models and metadata governance.
• Work with Snowflake, Databricks, Redshift, and similar platforms.
• Develop high-quality, tested code in SQL and Python.
• Integrate pipelines with cloud messaging, compute, and storage services.
• Apply data quality checks, monitoring, and error handling.
• Support CI/CD-enabled data deployments and documentation.

Skills

Data engineering

SQL

Python

ETL/ELT

Data modeling

Data orchestration

Batch and near-real-time processing

Agile/Scrum

Mentoring

Education

BA/BS or MS/MA in a related field

Tools

AWS

Snowflake

Databricks

AWS Redshift

CI/CD tooling

Job description

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 maps, 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.
• 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
• SQL
• Python
• ETL / ELT
• 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
• Disaster recovery
• Infrastructure as Code
• Federal or regulated-environment experience

Preferred Certifications

• 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.