Ignite 33

Data Engineering Lead

Suitland-Silver Hill, Maryland, United States

No sponsorshipDetected 147 days ago

PythonPostgreSQLAWSTerraformCI/CDData EngineeringCybersecurityAgileSASLeadershipCollaboration

About the role

Replace file-driven batch dependencies with: API-based ingestion Event-driven workflows Database-backed storage (e.g., Aurora/Postgres) Define canonical data schemas and transformation standards.

Legacy Data Discovery & Data Model Transformation Participate in structured system inventory efforts to document: Legacy file-based storage structures SAS dataset dependencies Subsystem data flows Manual gating and handoff processes Analyze legacy storage models and design target-state data models aligned to AWS Cloud Native architecture.
Cloud-Native Data Architecture Design Architect scalable AWS data pipelines using services such as: S3 Glue Lambda EventBridge SNS/SQS Aurora/Postgres Batch Athena Design data ingestion, staging, transformation, and validation workflows.
Optimize data storage for performance, scalability, and cost efficiency.
Expert Python-Based Data Engineering Develop advanced Python-based data transformation and validation pipelines.
Support regression validation through golden datasets and automated comparisons.
Support orchestration of gated workflows through automated triggers rather than manual file exchanges.
Collaborate across workstreams to establish shared data standards.
Support infrastructure-as-code alignment (Terraform/CloudFormation collaboration).
Architecture review boards Interface control documents Data flow diagrams Support ATO-related data validation evidence.
Experience developing data models for high-volume, data-intensive applications.

8+ years of experience in data engineering or data architecture.
Expert-level proficiency in Python for data engineering.
Demonstrated experience transforming legacy file-based systems into cloud-native data architectures.
Deep experience with AWS data services (Glue, Lambda, S3, Aurora/Postgres, EventBridge, etc.).
Experience designing scalable ETL/ELT pipelines.
Experience implementing automated data validation and quality controls.
Experience working in Agile Scrum Teams.
U.S. Citizenship required.
Expert-level proficiency in Python and strong experience designing AWS-based data architectures are required.
Required Qualifications 8+ years of experience in data engineering or data architecture.

Experience modernizing SAS-based data environments.
Experience supporting system-of-systems integration programs.
Experience implementing data lineage and metadata management.
Experience operating in regulated or federal environments.
Ignite IT is an Equal Employment Opportunity/Affirmative Action Employer.
Applicants selected may be required to possess and maintain a government clearance US CITIZENSHIP REQUIRED

Cloud-Native Data
Establish schema management, versioning, and data lineage practices.
Support serverless and containerized data processing architectures.
Implement modular, reusable data processing components.
Optimize large-scale data manipulation for distributed execution.
Develop high-performance ETL/ELT frameworks.
Embed automated validation checks directly into data pipelines.
Functional equivalence during migration Record-level and aggregate-level consistency Downstream compatibility across subsystems

Data accuracy metrics Pipeline health indicators Variance detection summaries Enable transparency into data transformation impacts across modernization phases.

This listing is sourced directly from Ignite 33's careers page and normalized into a canonical job model.