Remote Python/Data engineer jobs

We are looking to hire highly capable data engineers with working experience as a Python developer. You will be required to build an effective data architecture, create data engineering pipelines, maintain large-scale data systems, and streamline data processing.

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Job description

Job responsibilities

  • Automate common file system tasks & build API integrations to handle large databases
  • Build high-performance databases, and improve data models
  • Implement data security and protection practices
  • Write unit/integration tests to maintain accuracy in the data models
  • Perform data analysis and implement solutions to improve processes

Minimum requirements

  • Bachelor’s/Master’s degree in Computer Science (or equivalent experience)
  • 3+ years of experience as Data Engineer/similar roles (rare exceptions for skilled devs)
  • Proficiency in Python development
  • Experience with SQL, dimensional data modeling, and schema design
  • Experience with common data science toolkits like NumPy, Pandas, SciPy, etc.
  • Experience with programming languages such as R, MATLAB, etc.
  • Good understanding of applied statistics: regression, distributions, statistical testing, etc.
  • Fluency in English to collaborate with engineering managers
  • The ability to work full-time (40 hours/week) with a 4 hour overlap with U.S. time zones

Preferred skills

  • Experience with Agile Software Development methodologies
  • Excellent problem-solving and troubleshooting skills
  • Experience with building, and maintaining data processing systems
  • Working knowledge of NoSQL is a plus

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How to become a Python-data engineer?

Data engineers need to have a strong command of scripting languages like Python to solve complex problems on a coding level. Python-data engineering jobs responsibilities include building, maintaining data pipelines, warehousing Big Data, etc. are the most insightful information from the raw data.

Remote Python-data engineering jobs are seeing an exponential increase as more and more companies worldwide lean towards data. If you have gained expertise and fine-tuned your data science skills, you can be a top Python-data engineer. Data engineering offers the opportunity to bag a secure, high-paying remote job.

What is the scope in Python-data engineering?

Python-data engineering jobs are not always entry-level roles, but you can shift to managerial positions or become a data architect or machine learning engineer after a few years of experience and vast expertise. Even data engineers may also start their careers as software engineers or BI analysts.

As long as companies accumulate and process huge data sets, data engineering jobs will be in demand. While data engineering jobs are the top trending jobs in the technology industry, LinkedIn further listed Python-data engineering jobs in the list of jobs on the rise in 2021 and in the years to come.

Data engineers play a vital role in an organization’s progress. They create scalable solutions with their Python programming and problem-solving skills.

What are the roles and responsibilities of Python-data engineers?

Typically Python-data engineering jobs responsibilities are focused on developing and maintaining an organization’s data infrastructure that includes databases, data warehouses, and data pipelines. A data engineer primarily needs to transform data into a format that is actionable for analysis.

The data transformation cycle starts with cleaning, organizing, processing raw, and unorganized data. Next comes the data pipelines that refer to the configuration of the data processing and data storage systems. In this cycle, data engineers design and deploy systems to collect raw data from a SaaS platform or email marketing tool, clean, transform, and route data to destination systems, and store it in a data warehouse. Later, these data can be easily analyzed by data scientists using analytics and BI tools.

Though the primary task for data engineers is managing and organizing data, they also need to stay updated with the latest trends or deviations that may strike business goals. Overall, this is an exclusive technical position, which requires extensive knowledge and experience in programming, mathematics, and computer science. And specifically for the Python-data engineering jobs, the engineers need to have an exceptional grasp of the Python programming language.

Data engineers have to collaborate with other members, including data architects, data analysts, and data scientists, to research and discover new data accumulation methods and more efficient utilization for existing data.

Thus, Python-data engineers should be able to perform some common tasks when working with data, like -

  • Collecting datasets that align with business requirements
  • Developing algorithms to convert data into useful and insightful information
  • Building, testing, and sustaining database pipeline architectures
  • Collaborating with management to recognize company objectives
  • New method development for data validation and data analysis tools
  • Ensuring agreement with data management and security policies

How to become a Python-data engineer?

Let's move on to the path that one must take to pursue a profession in the Python-data engineering jobs field. To begin, keep in mind, you need to be formally educated with a major in mathematics, statistics, computer science, or any relevant subject to become a data engineer. Other than this, you also need command of the relevant technical and non-technical skills. Fresher data engineers may get jobs in start-ups and smaller businesses where they will work in all the areas of data engineering.

However, you may have heard that to get remote Python-data engineering jobs, you must have 3-5 years of experience. It is true for a couple of reasons.
First, industry experience allows you to recognize the vast opportunities while working remotely in top Silicon Valley companies.
Second, many organizations hire candidates with a proven track record to ensure a risk-free, fruitful hire.

Now, let's look at the skills and practices you'll need to master to join the league of remote data engineers.

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Skills required to become a Python-data engineer

The first step is learning the fundamental skills that can get you high-paying remote Python-data engineering jobs. Let’s take a look at what you need to know!

1. Coding

Proficiency in coding with Python programming language is essential to bag Python-data engineering jobs. Besides Python, knowledge in other common programming languages, including Java, R, Scala, SQL, NoSQL, etc., is a plus.

2. Relational and non-relational databases

Knowledge of databases is crucially important as it is one of the most common solutions for data storage. A prospective Python-data engineer should have familiarity with both relational and non-relational databases and their work process.

3. ETL (Extract, Transform, Load) systems

Through the ETL system, data is moved from databases and other sources to a single repository, like a data warehouse. Therefore, the data engineers must master the common ETL tools, such as Xplenty, Stitch, Alooma, and Talend.

4. Automation and scripting

Automation is essential when working with Big Data. As organizations need to collect information from the raw data and perform repetitive tasks, they hire efficient data engineers who write effective scripts to automate these tasks.

5. Big Data tools

Data engineers not only work with regular data, but they are also responsible for managing Big Data. New tools and technologies are emerging and different organizations have different preferences; therefore, the data engineers need to master popular Big Data tools, like Hadoop, MongoDB, and Kafka.

6. Programming languages

Python is the top programming language used for statistical analysis and modeling, whereas Java is used in data architecture frameworks. Scala is an extension of the Java language and is interoperable with Java.

7. Algorithms and data structures

Though the Python-data engineering jobs focus on data filtration and data optimization, basic knowledge of algorithms helps understand the larger scenario of the organization’s overall data function. It also helps in defining checkpoints and end goals for the business problem at hand.

Interested in remote Python-data engineering jobs?

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How to get remote Python-data engineering jobs?

Data engineers need to work hard enough to stay updated with all the recent trends and market aberrations and grow their skills gradually over time. In order to excel at their profession, they have to practice effectively and consistently. In that regard, there are two major factors that engineers must focus on to progress. They might get support from someone who is more experienced and effective in training new techniques while they are practicing. Further, as a data engineer, it's vital to fine-tune your analysis, computer engineering, and big data skills, so make sure there is someone who will help you out and keep an eye on your progress.

Turing offers the best remote Python-data engineering jobs that suit your career trajectories as a Python-data engineer. Grow rapidly by working on challenging technical and business problems on the latest technologies. Join a network of the world's best developers & get full-time, long-term remote Python-data engineering jobs with better compensation and career growth.

Why become a Python-data engineer at Turing?

Elite U.S. jobs

Long-term opportunities to work for amazing, mission-driven U.S. companies with great compensation.

Career growth

Work on challenging technical and business problems using cutting-edge technology to accelerate your career growth.

Exclusive developer community

Join a worldwide community of elite software developers.

Once you join Turing, you’ll never have to apply for another job.

Turing's commitments are long-term and full-time. As one project draws to a close, our team gets to work identifying the next one for you in a matter of weeks.

Work from the comfort of your home

Turing allows you to work according to your convenience. We have flexible working hours and you can work for top U.S. firms from the comfort of your home.

Great compensation

Working with top U.S. corporations, Turing developers make more than the standard market pay in most nations.

How much does Turing pay for their Python-data engineers?

At Turing, every data engineer is allowed to set his/her rate. However, Turing will recommend a salary at which we know we can find a fruitful and long-term opportunity for you. Our Python-data engineering jobs recommendations are based on our assessment of market conditions and the demand that we see from our elite customers.

Frequently Asked Questions

The job of a Python engineer is to write server-side web application logic. Their prime work is to integrate the Python software with an existing system or testing existing code to remove the bugs present by writing efficient and scalable Python codes. They assist the front-end developers and work on connecting applications with third-party web services.

Having substantial expertise in Python may or may not be enough depending on the company and the job role you are applying for. It's always a good practice to upskill and learn JavaScript, HTML, and CSS, as these languages are used to create web applications. Besides that, communicate with other people in developer communities and glance through the job descriptions of Python developers. If you are proficient with Python and looking to work from the comfort of your home, sign up at Turing.

Turing is an AGI infrastructure company specializing in post-training large language models (LLMs) to enhance advanced reasoning, problem-solving, and cognitive tasks. Founded in 2018, Turing leverages the expertise of its globally distributed technical, business, and research experts to help Fortune 500 companies deploy customized AI solutions that transform operations and accelerate growth. As a leader in the AGI ecosystem, Turing partners with top AI labs and enterprises to deliver cutting-edge innovations in generative AI, making it a critical player in shaping the future of artificial intelligence.

To become a Python engineer, learn HTML, CSS, and web frameworks. Acquire knowledge of databases like SQLite, MySQL, and skills to write Python scripts with server-side web logic. Have a good grip on Tkinter, a software used for GUI-based web applications. Once you're confident, sign up at Turing and land up a job at the Top U.S. companies as a Python engineer.

Having hands-on experience in coding, command line, creating ETL pipelines, proficiency at cloud services to work with data is sufficient to get a job. However, it depends upon the company as they could be looking for a specific skill set too. Be well prepared to answer the tech questions in the interview and glance at the job description of data engineers to get a clear idea. Along with that, take the Turing test to get exciting remote job offers in the Top U.S. companies.

We, at Turing, hire remote developers for over 100 skills like React/Node, Python, Angular, Swift, React Native, Android, Java, Rails, Golang, PHP, Vue, among several others. We also hire engineers based on tech roles and seniority.

Yes, the demand for people skilled in the Python programming language is high in the market. Python is not only an easy and simple language to handle but also has a user-friendly syntax wherein it has an abundance of libraries and frameworks. As a cross-platform language coupled with other benefits it holds that profit a firm, you can land a remote Python engineer job and work with elite Silicon Valley companies.

As per LinkedIn's emerging job reports and burning glass nova platform, data engineering is one of the fastest-growing jobs in recent years. One major statement would be focusing on how the demand for Data engineers is the growth in Big data. Companies like Accenture and Cognizant are hiring data engineers. If you are looking for a well-paying job as a Data engineer, visit Turing.com.

Our unique differentiation lies in the combination of our core business model and values. To advance AGI, Turing offers temporary contract opportunities. Most AI Consultant contracts last up to 3 months, with the possibility of monthly extensions—subject to your interest, availability, and client demand—up to a maximum of 10 continuous months. For our Turing Intelligence business, we provide full-time, long-term project engagements.

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In a nutshell, Turing aims to make the world flat for opportunity. Turing is the brainchild of serial A.I. entrepreneurs Jonathan and Vijay, whose previous successfully-acquired AI firm was powered by exceptional remote talent. Also part of Turing’s band of innovators are high-profile investors, such as Facebook's first CTO (Adam D'Angelo), executives from Google, Amazon, Twitter, and Foundation Capital.

Equal Opportunity Policy

Turing is an equal opportunity employer. Turing prohibits discrimination and harassment of any type and affords equal employment opportunities to employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, age, disability status, protected veteran status, or any other characteristic protected by law.

Explore remote developer jobs

briefcase
Python Automation and Task Creator

About Turing:

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.


Role Overview

We are seeking a detail-oriented Computer-Using Agent (CUA) to perform structured automation tasks within Ubuntu-based virtual desktop environments. In this role, you will interact with real desktop applications using Python-based GUI automation tools, execute workflows with high accuracy, and document every step taken.

This is a hands-on execution role ideal for candidates who are comfortable working with Linux systems, virtualization tools, and repeatable task workflows in a controlled environment.


What Does the Day-to-Day Look Like?

  • Set up and operate Ubuntu virtual machines using VMware or VirtualBox
  • Automate mouse and keyboard interactions using Python-based GUI automation (e.g., PyAutoGUI)
  • Execute predefined workflows across various Ubuntu desktop applications
  • Ensure tasks are completed accurately and can be reproduced consistently
  • Capture and document all actions, steps, and outcomes in a structured format
  • Collaborate with the delivery team to refine automation scenarios and workflows

Required Skills & Qualifications

  • Hands-on experience with Ubuntu/Linux desktop environments
  • Working knowledge of PyAutoGUI or similar GUI automation frameworks
  • Basic Python scripting and debugging skills
  • Familiarity with VMware or VirtualBox
  • Strong attention to detail and ability to follow step-by-step instructions
  • Clear documentation and reporting skills

Application Domains

You will be expected to perform automation tasks across the following Ubuntu-based environments:

  • os – Core Ubuntu desktop environment
  • chrome – Ubuntu with Google Chrome
  • gimp – Ubuntu with GIMP
  • libreoffice_calc – LibreOffice Calc
  • libreoffice_writer – LibreOffice Writer
  • libreoffice_impress – LibreOffice Impress
  • thunderbird – Thunderbird email client
  • vlc – VLC media player
  • vs_code – Visual Studio Code

Perks of Freelancing With Turing

  • Fully remote work.
  • Opportunity to work on cutting-edge AI projects with leading LLM companies.

Offer Details:

  • Commitments Required: 40 hours per week with 4 hours of overlap with PST. 
  • Engagement  type  : Contractor assignment (no medical/paid leave)
  • Duration of contract : 2 month
Holding Companies & Conglomerates
10K+ employees
Python
briefcase
Knowledge Graph Expert (Knowledge Graph / SQL / LLM)
About the Client

Our mission is to bring community and belonging to everyone in the world. We are a community of communities where people can dive into anything through experiences built around their interests, hobbies, and passions. With more than 50 million people visiting 100,000+ communities daily, it is home to the most open and authentic conversations on the internet.

About the Team

The Ads Content Understanding team’s mission is to build the foundational engine for interpretable and frictionless understanding of all organic and paid content on our platform. Leverage state-of-the-art applied ML and a robust Knowledge Graph (KG) to extract high-quality, monetization-focused signals from raw content — powering better ads, marketplace performance, and actionable business insights at scale.

We are seeking a Knowledge Graph Expert to help us grow and curate our KG of entities and relationships, bringing it to the next level.


About the Role


We are looking for a detail-oriented and strategic Knowledge Graph Curator. In this role, you will sit at the intersection of AI automation and human judgment. You will not only manage incoming requests from partner teams but also proactively shape the growth of our Knowledge Graph (KG) to ensure high fidelity, relevance, and connectivity. You will serve as the expert human-in-the-loop, validating LLM-generated entities and ensuring our graph represents the "ground truth" for the business.

 

Key Responsibilities


  • Onboarding of new entities to the Knowledge Graph maintained by the Ads team
  •  Data entry, data labeling for automation of content understanding capabilities
  • LLM Prompt tuning for content understanding automation

What You'll Do


1. Pipeline Management & Prioritization

  • Manage Inbound Requests: Act as the primary point of contact for partner teams (Product, Engineering, Analytics) requesting new entities or schema changes.
  • Strategic Prioritization: Triage the backlog of requests by assessing business impact, urgency, and technical feasibility.

2. AI-Assisted Curation & Human-in-the-Loop

  • Oversee Automation: Interact with internal tooling to review entities generated by Large Language Models (LLMs). You will approve high-confidence data, edit near-misses, and reject hallucinations.
  • Quality Validation: Perform rigorous QA on batches of generated entities to ensure they adhere to the strict ontological standards and factual accuracy required by the KG.
  • Model Feedback Loops: Participate in ad-hoc labeling exercises (creation of Golden Sets) to measure current model quality and provide training data to fine-tune classifiers and extraction algorithms.

3. Data Integrity & Stakeholder Management

  • Manual Curation & Debugging: Investigate bug reports from downstream users or automated anomaly detection systems. You will manually fix data errors, merge duplicate entities, and resolve conflicting relationships.
  • Feedback & Reporting: Close the loop with partner teams. You will report on the status of their requests, explain why certain modeling decisions were made, and educate stakeholders on how to best query the new data.


Qualifications for this role:

  • Knowledge Graph Fundamentals: Understanding of graph concepts (Nodes, Edges, Properties)
  • Taxonomy & Ontology: Experience categorizing data, managing hierarchies, and understanding semantic relationships between entities.
  • Data Literacy: Proficiency in navigating complex datasets. Experience with SQL, SPARQL, or Cypher is a strong plus.
  • AI/LLM Familiarity: Understanding of how Generative AI works, common failure modes (hallucinations), and the importance of ground-truth data in training.

Operational & Soft Skills

  • Analytical Prioritization: Ability to look at a list of 50 tasks and determine the 5 that will drive the most business value.
  • Attention to Detail: An "eagle eye" for spotting inconsistencies, typos, and logical fallacies in data.
  • Stakeholder Communication: Ability to translate complex data modeling concepts into clear language for non-technical product managers and business stakeholders.
  • Tool Proficiency: Comfort learning proprietary internal tools, ticketing systems (e.g., Jira), and spreadsheet manipulation (Excel/Google Sheets).


Offer Details


  • Full-time contractor or full-time employment, depending on the country
  • Remote only, full-time dedication (40 hours/week)
  • 8 hours of overlap with Netherlands
  • Competitive compensation package.
  • Opportunities for professional growth and career development.
  • Dynamic and inclusive work environment focused on innovation and teamwork
Media & Internet
251-10K employees
LLMSQL
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