Full-Time

Data Engineer

Elasticsearch + Datawarehousing

Particle41

Particle41

51-200 employees

Provides expert application, DevOps, ML teams

No salary listed

Remote in India

Remote

Category
Data & Analytics (1)
Required Skills
Scikit-learn
Bash
Microsoft Azure
Python
MySQL
Git
Apache Spark
SQL
Machine Learning
Java
Postgres
Microservices
AWS
Pandas
Elasticsearch
Redis
REST APIs
Flask
OpenCV
Linux/Unix
Databricks
Google Cloud Platform
Requirements
  • Bachelor's degree in Computer Science, Engineering, or related field.
  • Proven experience as a Data Engineer, with a minimum of 3 years of experience.
  • Proficiency in Elasticsearch and Python programming language is a must.
  • Experience with database technologies such as SQL (e.g., MySQL, PostgreSQL) and NoSQL (e.g., MongoDB) databases.
  • Strong understanding of Programming Libraries/Frameworks and technologies such as Flask, API frameworks, Data warehousing/lakehouse, Principles, Database, ORM, Data analysis, Databricks, Pandas, Spark, PySpark, Machine learning, OpenCV, Scikit-learn.
  • Utilize Java to build and enhance backend systems, particularly for integration with Elasticsearch and databases.
  • Develop APIs, microservices, and automation scripts as needed.
  • Utilities & Tools: logging, requests, subprocess, regex, pytest
  • ELK stack, Redis, distributed task queues
  • Strong understanding of data warehousing/lakehousing principles and concurrent/parallel processing concepts.
  • Familiarity with at least one cloud data engineering stack (Azure, AWS, or GCP) and the ability to quickly learn and adapt to new ETL/ELT tools across various cloud providers.
  • Familiarity with version control systems like Git and collaborative development workflows.
  • Competence in working on Linux OS and creating shell scripts.
  • Solid understanding of software engineering principles, design patterns, and best practices.
  • Excellent problem-solving and analytical skills, with a keen attention to detail.
  • Effective communication skills, both written and verbal, and the ability to collaborate in a team environment.
  • Adaptability and willingness to learn new technologies and tools as needed.
Responsibilities
  • Design, implement, and optimize Elasticsearch clusters for high-performance querying and data retrieval.
  • Build and manage Elasticsearch indexes, ensuring data is stored, indexed, and queried efficiently.
  • Build and optimize data storage solutions like data lakes and warehouses.
  • Integrate structured and unstructured data from various internal and external systems to create a unified view for analysis.
  • Ensure data accuracy, consistency, and completeness through rigorous validation, cleansing, and transformation processes.
  • Maintain comprehensive documentation for data processes, tools, and systems while promoting best practices for efficient workflows.
  • Collaborate with product managers, and other stakeholders to gather requirements and translate them into technical solutions.
  • Participate in requirement analysis sessions to understand business needs and user requirements.
  • Provide technical insights and recommendations during the requirements-gathering process.
  • Participate in Agile development processes, including sprint planning, daily stand-ups, and sprint reviews.
  • Work closely with Agile teams to deliver software solutions on time and within scope.
  • Adapt to changing priorities and requirements in a fast-paced Agile environment.
  • Conduct thorough testing and debugging to ensure the reliability, security, and performance of applications.
  • Write unit tests and validate the functionality of developed features and individual elements.
  • Writing integration tests to ensure different elements within a given application function as intended and meet desired requirements.
  • Identify and resolve software defects, code smells, and performance bottlenecks.
  • Stay updated with the latest technologies and trends in full-stack development.
  • Propose innovative solutions to improve the performance, security, scalability, and maintainability of applications.
  • Continuously seek opportunities to optimize and refactor existing codebase for better efficiency.
  • Stay up-to-date with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Collaborate effectively with cross-functional teams, including testers, and product managers.
  • Foster a collaborative and inclusive work environment where ideas are shared and valued.
Desired Qualifications
  • Bachelor's degree in Computer Science, Engineering, or related field.
  • Proven experience as a Data Engineer, with a minimum of 3 years of experience.
  • Proficiency in Elasticsearch and Python programming language is a must.
  • Experience with database technologies such as SQL (e.g., MySQL, PostgreSQL) and NoSQL (e.g., MongoDB) databases.
  • Strong understanding of Programming Libraries/Frameworks and technologies such as Flask, API frameworks, Data warehousing/lakehouse, Principles, Database, ORM, Data analysis, Databricks, Pandas, Spark, PySpark, Machine learning, OpenCV, Scikit-learn.
  • Utilize Java to build and enhance backend systems, particularly for integration with Elasticsearch and databases.
  • Develop APIs, microservices, and automation scripts as needed.
  • Utilities & Tools: logging, requests, subprocess, regex, pytest
  • ELK stack, Redis, distributed task queues
  • Strong understanding of data warehousing/lakehousing principles and concurrent/parallel processing concepts.
  • Familiarity with at least one cloud data engineering stack (Azure, AWS, or GCP) and the ability to quickly learn and adapt to new ETL/ELT tools across various cloud providers.
  • Familiarity with version control systems like Git and collaborative development workflows.
  • Competence in working on Linux OS and creating shell scripts.
  • Solid understanding of software engineering principles, design patterns, and best practices.
  • Excellent problem-solving and analytical skills, with a keen attention to detail.
  • Effective communication skills, both written and verbal, and the ability to collaborate in a team environment.
  • Adaptability and willingness to learn new technologies and tools as needed.

Particle41 builds expert teams in application development, DevOps, and machine learning to strengthen a client’s capabilities. They assemble cross-functional teams that integrate into a client’s projects, guiding work with velocity, visibility, and vision to accelerate delivery. They differentiate themselves by providing specialized, high-caliber teams tailored to client needs and emphasizing clear communication and ongoing capability building rather than generic consulting. The goal is to amplify a client’s business by delivering dependable, expert teams that quickly advance critical development, operations, and ML initiatives.

Company Size

51-200

Company Stage

N/A

Total Funding

N/A

Headquarters

Frisco, Texas

Founded

2015

Simplify Jobs

Simplify's Take

What believers are saying

  • AI-native toolchains enable faster timelines and lower costs, capturing market share from traditional consultancies.
  • Fractional CTO demand grows as mid-market companies need technology leadership without full-time hires.
  • Data engineering and DevOps optimization services expand TAM across healthcare, fintech, and enterprise sectors.

What critics are saying

  • Open-source AI tools like Devin and GitHub Copilot commoditize code generation, eroding premium pricing.
  • Thoughtworks' 5,000+ experts and $500M+ scale undercut Particle41 in enterprise DevOps and AI consulting.
  • Revenue discrepancy between ZoomInfo ($23.7M) and Bitscale ($14.3M) signals investor skepticism and funding risk.

What makes Particle41 unique

  • AI-augmented teams pair senior engineers with AI agents for accelerated delivery and cost reduction.
  • Fractional CTO services provide C-suite aligned technology leadership for enterprise clients.
  • Legacy modernization expertise delivers 60% latency reduction and 40% cost savings via cloud migration.

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Benefits

Health Insurance

401(k) Retirement Plan

Remote Work Options

Flexible Work Hours

Paid Vacation

Paid Holidays

Professional Development Budget

Conference Attendance Budget

Wellness Program

Mental Health Support

Gym Membership

Phone/Internet Stipend

Home Office Stipend

Family Planning Benefits

Fertility Treatment Support

Stock Options

Company Equity