Mid-Level Python Data Engineer [$320k/yr+] TS/SCI-FS Poly

SYSTOLIC, INC.

Herndon, VA, United States

about 1 month ago

Apply on www.clearancejobs.com

Prepare application

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

8 years minimum

Compensation

$320,000.0

Working hours

Regular working hours

Job source

www.clearancejobs.com

Tech stack

Java (Programming Language) Artificial Intelligence Amazon Web Services Apache HTTP Server Bash Shell Databases System Configuration Custom Software Information Engineering Extract Transform Load (ETL) Software Debugging Software Design Patterns

+21 more

Amazon DynamoDB Python (Programming Language) PostgreSQL MySQL Operational Databases Performance Tuning Query Optimization Azure Machine Learning Software Deployment SQL Databases Data Streaming Workflow Management Systems Data Processing Cloud Platform System Apache Spark Git Containerization Data Lineage Terraform Data Pipelines Docker

Job description

Build complex data flows, production data pipelines, and ETL workflows.
Develop with Python, Java, SQL, and Bash scripting.
Utilize orchestration tools for Apache Spark jobs, containerize applications with Docker in AWS environments.
Manage MySQL, PostgreSQL, and DynamoDB databases.
Implement code control with Git and Infrastructure as Code with Terraform.
Integrate AI/ML services and work with Apache Iceberg and Trino.
Understand data requirements and contribute to documentation., * Work with a small team to build complex data flows for custom applications.
Build end-to-end data pipelines leveraging advanced Python programming skills.
Utilize orchestration tools to deploy and manage data pipelines, including configuring and updating Spark Jobs.
Containerize and deploy applications in cloud environments like AWS.
Manage and optimize databases such as MySQL and PostgreSQL, including performance tuning, schema design, and query optimization for complex, analytical workloads.
Leverage industry standard tools for code control (Git, IaaC control) and Infrastructure as Code (Terraform).
Work with data catalogs, track data lineage, and handle various data formats, including Geospatial.
Employ Bash scripting for automation and data processing tasks.
Integrate AI/ML services and models.
Collaborate with stakeholders to understand data requirements, assess feasibility, and design solutions with minimal oversight.
Apply strong problem-solving and debugging skills for data quality issues, pipeline failures, and performance bottlenecks.
Contribute to data engineering documentation, best practices, and design patterns.
Familiarity with Java, DynamoDB, Apache Iceberg, and Trino is beneficial.