Hybrid Data Engineer

Jobtailor; Hanover (MD); On-site; USD 110,000 - 140,000; Full time

Job summary

Jobtailor in the United States is seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines across cloud and on-prem environments. You will collaborate with analytics and AI teams to prepare datasets for models and ensure data quality and security at scale.

Required: 4+ years in data engineering or backend software, security clearance, and strong Python/SQL/Java skills, plus experience with Snowflake, Redshift, Spark, Databricks, Kafka, Airflow and cloud

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or Data Engineering.
• 4+ years of progressive professional experience in a data engineering or backend software engineering role.
• Security clearance required (Secret or higher).
• Strong proficiency in Python, SQL, Java.
• Experience with cloud data warehouses such as Snowflake and AWS Redshift.
• Familiarity with distributed computing tools like Spark, Databricks, and Kafka.
• Experience with Azure Data Factory, AWS Glue, or similar data integration platforms.
• Experience with workflow management tools like Apache Airflow.
• Hands-on experience with AWS, GCP, or Azure cloud environments.
• Familiarity with multi-cloud data ecosystem patterns.
• Experience integrating structured and unstructured data sources. Knowledge of schema design, data modeling, and cloud-based storage patterns.

Responsibilities

• Design, construct, install, test, and maintain highly scalable data management systems and robust ELT/ETL pipelines across cloud and on-prem systems.
• Build infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using cloud technologies. Support API strategy, data modeling, and domain-driven data structures.
• Implement monitoring systems to ensure data integrity, quality, and security across all storage and processing layers. Implement data quality checks, validation, lineage tracking, and metadata management.
• Prepare and optimize data for AI/ML models, semantic search, analytics, and mission applications.
• Identify, design, and implement internal process improvements, such as automating manual processes and optimizing data delivery for greater scalability. Automate ingestion and transformation processes using industry-standard tools and patterns. Troubleshoot pipeline issues and optimize for performance and cost.
• Work with analytics and business teams to understand their data requirements and deliver production-ready datasets. Collaborate with AI engineers and analysts to ensure datasets meet requirements.

Skills

Python

SQL

Java

Data Engineering

Data Modeling

Data Integration

Schema Design

Data Pipeline Optimization

Data Quality Checks

Metadata Management

Automation of Data Processes

Education

Bachelor's degree in Computer Science, Information Technology, or Data Engineering

Job description

Responsibilities

• Design, construct, install, test, and maintain highly scalable data management systems and robust ELT/ETL pipelines across cloud and on-prem systems.
• Build infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using cloud technologies. Support API strategy, data modeling, and domain-driven data structures.
• Implement monitoring systems to ensure data integrity, quality, and security across all storage and processing layers. Implement data quality checks, validation, lineage tracking, and metadata management.
• Prepare and optimize data for AI/ML models, semantic search, analytics, and mission applications.
• Identify, design, and implement internal process improvements, such as automating manual processes and optimizing data delivery for greater scalability. Automate ingestion and transformation processes using industry-standard tools and patterns. Troubleshoot pipeline issues and optimize for performance and cost.
• Work with analytics and business teams to understand their data requirements and deliver production-ready datasets. Collaborate with AI engineers and analysts to ensure datasets meet requirements.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Data Engineering
• 4+ years of progressive professional experience in a data engineering or backend software engineering role
• Security clearance required (Secret or higher)
• Strong proficiency in Python, SQL, Java.
• Experience with cloud data warehouses such as Snowflake and AWS Redshift.
• Familiarity with distributed computing tools like Spark, Databricks, and Kafka.
• Experience with Azure Data Factory, AWS Glue, or similar data integration platforms.
• Experience with workflow management tools like Apache Airflow.
• Hands‑on experience with AWS, GCP, or Azure cloud environments. Familiarity with multi‑cloud data ecosystem patterns.
• Experience integrating structured and unstructured data sources. Knowledge of schema design, data modeling, and cloud-based storage patterns.

Hard Skills

• Data Engineering
• Backend Software Engineering
• Data Modeling
• Schema Design
• Data Quality Checks
• Metadata Management
• Automation of Data Processes
• Data Integration
• Cloud Data Warehousing
• Data Pipeline Optimization

Certifications & Qualifications

• Bachelor's Degree in Computer Science
• Security Clearance (Secret or Higher)