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Entry Level Startup Data Engineer Jobs in Washington

Hire Hangar

Data Engineer

Elkridge, MD · On-site

$160K - $200K/yr

Job Title| Data Engineer Location | Remote (US Only) Time Zone | US Time Zones (EST-PST) Role ... startup - Experience with AWS, GCP, Docker, or Kubernetes Tools & Technology: - Graph database ...

Hire Hangar

Data Engineer

Laurel, MD · On-site

$160K - $200K/yr

Job Title| Data Engineer Location | Remote (US Only) Time Zone | US Time Zones (EST-PST) Role ... startup - Experience with AWS, GCP, Docker, or Kubernetes Tools & Technology: - Graph database ...

Hire Hangar

Data Engineer

Columbia, MD · On-site

$160K - $200K/yr

Job Title| Data Engineer Location | Remote (US Only) Time Zone | US Time Zones (EST-PST) Role ... startup - Experience with AWS, GCP, Docker, or Kubernetes Tools & Technology: - Graph database ...

Inroads

Data Engineer I

Washington, DC · On-site +1

$85K/yr

About the Role We're hiring an entry-level Data Engineer to join our Data Engineering team. You'll take ownership of building reliable ELT/ETL pipelines and strong analytical data models using dbt.

Pwc

Data Engineer - Senior Associate

Washington, DC

$77K - $202K/yr

... a Data Engineer - Senior Associate, you will focus on designing and building data infrastructure ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Bechtel

Startup & Operations Coordinator

Reston, VA

$140K - $203K/yr

Supports aggregation and reporting of Business Unit-level CSU data * Interfaces with engineering, construction, quality, project controls, and client organizations * Collaborates with Project Startup ...

New

MSCCN

Field Service Engineer - Critical Power

Sterling, VA · On-site

$75K - $100K/yr

Perform installation, startup, and commissioning of lithium battery systems for data center and/or ... Prior field service or commissioning experience. Entry-level candidates are encouraged to apply ...

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Entry Level Startup Data Engineer information

What are some common challenges faced by entry level data engineers at startups, and how can they be addressed?

Entry level data engineers at startups often encounter challenges such as working with rapidly evolving tech stacks, limited documentation, and balancing multiple responsibilities due to smaller teams. Adapting quickly and proactively seeking clarification from team members is key. Building strong communication with software engineers, data scientists, and product managers helps ensure alignment on data requirements and project priorities. Taking initiative to document solutions and automate repetitive tasks can also improve efficiency and contribute to team success.

What does an Entry Level Startup Data Engineer do?

An Entry Level Startup Data Engineer is responsible for building and maintaining the data infrastructure that supports a startup's analytics and business operations. They typically work with databases, data pipelines, and cloud platforms to collect, process, and store data from various sources. Their tasks often include cleaning and transforming raw data, ensuring data quality, and assisting data analysts or scientists by providing them with reliable datasets. Because startups often have smaller teams, entry-level data engineers may also take on a variety of technical tasks and collaborate closely with software engineers and product managers. This role is ideal for those looking to gain broad experience in data engineering within a fast-paced, innovative environment.

What are the key skills and qualifications needed to thrive as an Entry Level Startup Data Engineer, and why are they important?

To thrive as an Entry Level Startup Data Engineer, you need a solid understanding of programming languages like Python or SQL, data modeling, and a relevant degree such as computer science or engineering. Familiarity with data pipelines, cloud platforms (e.g., AWS, Google Cloud), and tools like Apache Spark or ETL systems is typically required. Strong problem-solving abilities, adaptability, and effective communication skills help you excel in a fast-paced, evolving environment. These competencies are crucial for building reliable data solutions and collaborating well within lean startup teams.

What is the difference between Entry Level Startup Data Engineer vs Data Analyst?

AspectEntry Level Startup Data EngineerData Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; basic SQL, Python, or Spark knowledgeBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and visualization tools
Work EnvironmentStartups, fast-paced, collaborative, technical focus on data pipelines and infrastructureVarious industries, focus on data interpretation, reporting, and business insights
Employer & Industry UsageTech startups, SaaS companies, e-commerceFinance, marketing, healthcare, retail

Entry Level Startup Data Engineers focus on building data infrastructure and pipelines, requiring technical skills like SQL and Python. Data Analysts interpret data to generate insights, often using visualization tools. While both roles work with data, engineers develop the systems, and analysts analyze data for decision-making.

What are the most commonly searched types of Startup Data Engineer jobs in Washington? The most popular types of Startup Data Engineer jobs in Washington are:
What are popular job titles related to Entry Level Startup Data Engineer jobs in Washington? For Entry Level Startup Data Engineer jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Entry Level Startup Data Engineer jobs in Washington look for? The top searched job categories for Entry Level Startup Data Engineer jobs in Washington are:
Entry Level Startup Data Engineer jobs near you
Infographic showing various Entry Level Startup Data Engineer job openings in Washington as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Engineer

Hire Hangar

Elkridge, MD • On-site

$160K - $200K/yr

Contractor

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Join Hire Hangar and work with fast-growing global companies while building a long-term career.

Job Title| Data Engineer
Location | Remote (US Only)
Time Zone | US Time Zones (EST–PST)

Role Overview:
We are seeking a Software Engineer to help build and scale a graph-database-backed social listening platform. This role sits at the intersection of backend data infrastructure and front-end visualization, supporting a product that ingests high-volume social and web data in real time and visualizes complex network relationships. The ideal candidate is comfortable working across graph databases, streaming data pipelines, and modern front-end frameworks, and thrives in a fast-moving, early-stage engineering environment.

Key Responsibilities:
- Design, build, and maintain backend services that interface with graph databases to model and query complex relationship data
- Develop and maintain real-time data ingestion pipelines handling high-throughput social and web data
- Build and optimize web scraping and crawler infrastructure to support continuous data collection
- Develop front-end features and dashboards that visualize network and relationship data in an intuitive, performant way
- Collaborate cross-functionally to translate product requirements into scalable technical solutions
- Write clean, maintainable, well-tested code across the stack
- Troubleshoot performance bottlenecks across data ingestion, storage, and visualization layers

Required Qualifications:
- Hands-on experience with graph databases (such as Neo4j, TigerGraph, Dgraph, ArangoDB, or Amazon Neptune) and graph query languages (such as Cypher or Gremlin)
- Experience with real-time/streaming data infrastructure (such as Kafka, Kinesis, Flink, or Spark)
- Strong proficiency in at least one backend language such as Python, Go, or Node.js/TypeScript
- Front-end development experience with React, Next.js, and TypeScript
- Experience building or working with data pipelines, ETL processes, or web scraping/crawler infrastructure
- Comfortable working in a high-growth, early-stage engineering environment with evolving priorities
- Must be authorized to work in the United States without sponsorship

Preferred Qualifications:
-Experience with data visualization libraries such as D3, Cytoscape, Sigma.js, vis.js, or Recharts, particularly for graph/network visualizations
- Experience with social listening, social media data, or large-scale web data platforms
- Familiarity with Elasticsearch, OpenSearch, Redis, or Airflow
- Prior experience at a seed-to-Series B startup
- Experience with AWS, GCP, Docker, or Kubernetes

Tools & Technology:
- Graph database platforms (Neo4j, TigerGraph, Dgraph, ArangoDB, or similar)
- Streaming/data pipeline tools (Kafka, Spark, Flink, or similar)
- React, Next.js, TypeScript
- Python, Go, or Node.js
- Cloud infrastructure (AWS/GCP), Docker, Kubernetes

 
 
 
 

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Compensation Range: $160K - $200K