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Live In Data Collector Jobs in Washington, DC (NOW HIRING)

SZNS Solutions LLC

Data Engineer

Reston, VA · On-site

$119K - $143K/yr

We specialize in delivering agentic AI and cloud computing solutions. Founded by ex-Googlers with ... live and automated intelligence. Ultimately, you'll create the foundations that will influence key ...

MetroStar

Sr. Data Architect III (6550)

Washington, DC · Hybrid

$174K - $202K/yr

The ideal candidate brings deep expertise in data modeling, hybrid data environments, and secure ... live by our mission: A passion for our people. Value for our customers. If you think you can see ...

CAVA - Support Center

Data Analyst

Washington, DC

We are guided by a Mediterranean heritage that's beenperfecting how to eat and live for four ... Our best workhappens when we act in service of others. Constant Curiosity: We are eager to learn ...

CAVA

Data Analyst

Washington, DC

We are guided by a Mediterranean heritage that's beenperfecting how to eat and live for four ... Our best workhappens when we act in service of others. Constant Curiosity: We are eager to learn ...

MetroStar

Sr. Data Architect III (6550)

Washington, DC · On-site

$174K - $202K/yr

The ideal candidate brings deep expertise in data modeling, hybrid data environments, and secure ... live by our mission: A passion for our people. Value for our customers. If you think you can see ...

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All JobsLive In Data Collector JobsLive In Data Collector Jobs in Washington, DC

Live In Data Collector information

See Washington, DC salary details

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$32

How much do live in data collector jobs pay per hour?

As of Jun 13, 2026, the average hourly pay for live in data collector in Washington, DC is $22.88, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $27.21 per hour, depending on experience, location, and employer.

What is the difference between Live In Data Collector vs Field Data Technician?

AspectLive In Data CollectorField Data Technician
CredentialsHigh school diploma or equivalent; training in data collection methodsHigh school diploma; technical training or certifications often preferred
Work EnvironmentResidential settings, living on-site or nearbyVarious outdoor and indoor locations, traveling frequently
Employer & IndustryResearch firms, market research companies, government agenciesUtility companies, environmental agencies, research organizations

While both roles involve collecting data in the field, Live In Data Collectors typically reside on-site to gather specific information, often in residential settings. Field Data Technicians usually travel to multiple locations, working outdoors or in various environments. Both roles require similar credentials but differ mainly in work setting and living arrangements.

What are popular job titles related to Live In Data Collector jobs in Washington, DC? For Live In Data Collector jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Live In Data Collector jobs in Washington, DC look for? The top searched job categories for Live In Data Collector jobs in Washington, DC are:
Live In Data Collector jobs near you

Data Engineer

SZNS Solutions LLC

Reston, VA • On-site

$119K - $143K/yr

Full-time

Posted 27 days ago

Job description

"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

  • Competitive salary and benefits package
  • Hybrid work environment (MWF in-person in our Reston office)
  • A collaborative and innovative work environment
  • Continuous learning and development opportunities