Data Engineer, Journeyman

Sierra Management And Technologies Inc•California, MD

30d•Onsite

About The Position

Sierra Management and Technologies is recruiting for a Data Engineer to provide support for the NAWCAD Readiness & Fleet Analytics (R&FA) Division’s Advanced Analytics and Innovation (AA&I) Branch at Patuxent River Naval Air Station in Lexington Park, MD. This Data Engineer will primarily support migrating code for data science projects from Cloudera Data Science Workbench (CDSW) to Databricks. The Data Engineer will design, build, and maintain robust data pipelines and architectures that support advanced analytics and decision-making across the Naval Aviation Enterprise. The Data Engineer will focus on data engineering tasks, including data extraction, transformation, and loading (ETL), database management, and optimizing data workflows. Your work will directly support Program Management Air (PMA) offices, Air Systems Group, Command, Fleet Readiness Centers, and other Department of Defense (DoD) services. As a Data Engineer, you will leverage Python, SQL, and cloud-based platforms to ensure the seamless flow of data between systems and applications. You will play a critical role in enabling data-driven solutions by ensuring data integrity, scalability, and accessibility for analytics teams and stakeholders.

Requirements

A Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field with 5+ years of related academic or professional experience.
Proficiency in Python and SQL, with hands-on experience in developing ETL pipelines and managing databases.
Experience with cloud platforms such as AWS, Databricks, or similar tools.
Strong understanding of relational and non-relational database systems.
Proven experience migrating workflows and code from legacy platforms (e.g., CDSW) to modern cloud-based environments (e.g., Databricks).
Ability to translate existing workflows to new environments while ensuring results are consistent or improved in terms of performance and data quality.
Proficiency in HiveQL and Python for data engineering tasks.
Proficiency in GitLab and JIRA for project management and version control.
High-level problem-solving and interpersonal skills.
Flexible and able to work effectively in dynamic environments.
Strong oral and written communication skills, including the ability to interact professionally across all levels of management.
Proven ability to work collaboratively with cross-functional teams to deliver data solutions.
Secret security clearance.
U.S. Citizen and authorized to work in the U.S. without sponsorship.

Nice To Haves

Experience with Tableau, Qlik, or Power BI for creating advanced visualizations and interactive dashboards.
Experience with schema design and data modeling.
Familiarity with Apache Spark or Hadoop.
Experience implementing CI/CD pipelines for data engineering projects.
Familiarity with aviation industry data and experience in the aerospace and/or defense industries.
Adaptability to work effectively in dynamic environments.

Responsibilities

Migrate existing HiveQL and Python-based workflows from Cloudera Data Science Workbench (CDSW) to Databricks.
Translate existing workflows to the new environment while ensuring results are consistent or improved in terms of performance, scalability, and data quality.
Refactor and optimize code to leverage Databricks features and capabilities effectively.
Collaborate with analytics teams to validate migrated workflows and ensure functionality aligns with project requirements.
Leverage cloud platforms such as AWS, Databricks, or similar tools to manage and process large-scale datasets.
Implement CI/CD workflows for data engineering projects to streamline development and deployment.
Design, develop, and maintain ETL pipelines to extract, transform, and load data from various sources into centralized databases or data warehouses.
Automate data workflows and processes to ensure efficient and reliable data delivery.
Optimize data pipelines for scalability, performance, and fault tolerance.
Build and manage relational and non-relational databases to support analytics and reporting needs.
Write and optimize complex SQL queries for data extraction and manipulation.
Ensure data integrity, security, and accessibility across all systems.
Work closely with stakeholders, including product owners and analytics teams, to understand data requirements and deliver solutions that meet business needs.
Provide technical guidance and support to team members on data engineering best practices.

Benefits

Flexible work schedules and remote/hybrid opportunities (depending on the role)
Medical, dental, and vision insurance
Flexible spending account and health savings account options
Dependent care flexible spending account
Education reimbursement
Voluntary insurance such as short-term disability, hospital indemnity, critical illness, and accident insurance
100% company-paid life + AD&D and long-term disability insurance
Generous paid time off policy
11 paid holidays
401(k) retirement plan with matching contributions
Employee assistance program