Data Engineer

SZNS Solutions LLC•Reston, VA

4h•Hybrid

About The Position

The Data Engineer is the bedrock of intelligence operations, responsible for turning raw, unstructured data into actionable intelligence. You will embed directly with clients to build the data pipelines that power AI workflows. We build systems that don't just move data, but do it with the speed and reliability required for live and automated intelligence. Ultimately, you’ll create the foundations that will influence key strategic decisions for us and our customers.

Requirements

Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
5+ years of experience in data engineering, within a cloud environment, demonstrating a clear progression from engineering into architectural design
Proficiency in SQL and strong programming skills in Python, Rust, or Java
Experience building and maintaining data pipelines using processing/streaming frameworks (e.g., Kafka, Flink, Beam, Spark) and orchestration tools (e.g., Airflow)
Experience architecting data stores and schemas for AI workflows (e.g., RAG)
Active Google Cloud certifications, or willingness to obtain within one month of joining
Builder mentality and bias for action
US Citizen

Nice To Haves

Deep expertise in the Google Cloud Platform (GCP) ecosystem, specifically building streaming and batch pipelines using Dataflow (Apache Beam), Pub/Sub, BigQuery, and Cloud Composer (Airflow)
Strong background in data modeling and architecture across relational (e.g., PostgreSQL), NoSQL (e.g., Firestore, MongoDB), and graph databases (e.g., Neo4j), including modern cloud data warehouses (e.g., BigQuery) and data lakes (e.g., GCS, Dataproc)
Demonstrated experience setting up infrastructure for modern data science, machine learning, or Generative AI (e.g., preparing unstructured data, vector databases, RAG pipelines)
Familiarity with regulatory compliance frameworks (FedRAMP, HIPAA, etc.) and security strategies
Experience with modern data platforms like Snowflake or Databricks

Responsibilities

ETL/ELT Pipelines: Architect and deploy pipelines to ingest, transform, and store data from high volume, disparate sources for real-time analysis
Build for the Enterprise: Create a highly reliable single source of truth for enterprise intelligence and enablement
AI Workflow Enablement: Architect and optimize production-grade data foundations to support high-performance AI workflows and automated decision-making.
Operations & Governance: Establish and automate strict data security, quality assurance, and governance processes. Design systems for high fault tolerance and rapid disaster recovery
Efficiency: Design and model for efficient queries, resource usage, workload scheduling, and cost