Data Engineer

SZNS Solutions LLC Open · verified Oct 24, 2026

On-site Reston Full-time Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at SZNS Solutions LLC. Reston · full-time · no salary stated · we estimate $130,521–$145,808.

Estimated pay

SZNS Solutions LLC has not published a salary for this role. The figure below is our estimate, not theirs.

$130,521 – $145,808

What the middle half of mid-level data engineering roles in Reston paid, among postings that did state a salary.

Worked out from 5 postings that stated pay, median $140,000. Last updated Oct 20, 2026.

RoleData Engineering

SeniorityMid-level

LocationReston

WorkplaceOn-site

EmploymentFull-time

PostedApr 17, 2026 · 6mo ago

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Build pipelines that bring together high-volume, varied data for transformation and real-time analysis
Create dependable enterprise data stores that give AI workflows a consistent source of intelligence
Shape data foundations for AI applications and automated decisions, with production performance in mind
Set up security, data-quality and governance controls, plus fault recovery processes
Tune data models, queries, resource use and workload schedules to manage efficiency and cost

What you bring

At least five years in cloud data engineering, with growth from implementation work into architecture
A computer science or engineering degree, or equivalent hands-on experience
Strong SQL and programming ability in Python, Rust or Java, plus experience with pipeline and orchestration frameworks
Experience designing data stores and schemas for AI use cases such as RAG
You are a U.S. citizen and hold Google Cloud certifications, or can earn them within a month of starting

Who this fits

This mid-level, full-time role suits someone ready to design data architecture as well as build pipelines. You’ll work directly with clients and be in the Reston office on Monday, Wednesday and Friday.

From the employer

"SZNS Solutions (pronounced "seasons") is a technology consulting company and Google Cloud Partner based in Reston VA. We specialize in delivering agentic AI and cloud computing solutions. Founded by ex-Googlers with engineers from Google, Amazon, and Capital One, SZNS differentiates itself particularly in AI, data engineering, blockchain, and cloud-native software application development.”

Role Summary

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.

Key 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

Requirements

Minimum Qualifications

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

Preferred Qualifications

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

Benefits