Remote data platform engineer jobs

We, at Turing, are looking for highly-skilled remote data platform engineers who will be participating in architecture and implementation of cloud-native data pipelines and infrastructure to enable analytics and machine learning on rich datasets. Get an opportunity to work with the leading U.S. companies and rise quickly through the ranks.

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Job description

Job responsibilities

  • Build scalable data architecture, including data extractions and data transformation
  • Build cost-effective and strategic solutions by developing a clear understanding of data platform cost
  • Design and build data products and data flows for the continued expansion of the data platform
  • Write high-performant, well-styled, validated, and documented code
  • Participate in data cleansing and data quality initiatives
  • Build automated data engineering pipelines

Minimum requirements

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 3+ years of experience in data engineering (rare exceptions for highly skilled developers)
  • Experience of developing real-time data streaming pipelines using Change Data Capture (CDC), Kafka and Streamsets/NiFi/Flume/Flink
  • Proficient with big data technologies like Hadoop, Hive, etc.
  • Experience with Change Data Capture tooling such as IBM Infosphere, Oracle Golden Gate, Attunity, Debezium
  • Experience of ETL technical design, automated data quality testing, QA and documentation, data warehousing, data modeling and data wrangling
  • Expertise in Unix and DevOps automation tools like Terraform and Puppet and experience in deploying applications to at least one of the major public cloud provider such AWS, GCP or Azure
  • Extensive experience using RDMS and one of the NoSQL databases such as MongoDB, ETL pipelines, Python, Java APIs using spring boot and writing complex SQLs
  • Strong Python, Java and other backend development skills
  • Fluency in English language for effective communication
  • Ability to work full-time (40 hours/week) with a 4 hour overlap with US time zones

Preferred skills

  • Basic understanding of data systems or data pipelines
  • Knowledge of moving trained ML models into production data pipelines
  • A good understanding of cloud warehouse such as Snowflake
  • Grasp on modern code development practices
  • Experience with core AWS services and concepts (S3, IAM, autoscaling groups)
  • Basic DevOps knowledge
  • Knowledge of relational database modeling concepts and SQL skills
  • Strong analytical, consultative, and communication skills

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How to become a Data platform engineer ?

Data platform engineering is a broad topic that encompasses a range of titles, with a primary focus on constructing trustworthy infrastructures that allow for continuous data flow in a data-driven environment. These individuals serve as facilitators of clean and raw data from a variety of sources, allowing employees to use it to make data-driven decisions inside the firm.

The process of designing and building large-scale data collecting, storage, and analysis systems is known as Data platform engineering. It's a broad field with applications in nearly every industry. Organizations may collect massive amounts of data, but they need the right people and technology to ensure that the data reaches data scientists and analysts in usable form.

Data platform engineers create systems that collect, process and transform raw data into information that data scientists and business analysts can understand in a variety of situations. The ultimate goal is to make data more accessible to enterprises so they can evaluate and improve their performance.

What is the scope of Data platform engineering?

One of the most in-demand jobs in the industry is that of a remote Data platform engineer. Businesses regard them highly in all sectors, and they are handsomely paid for their work.

As more companies get on the Big Data bandwagon and mine data for relevant insights, the demand for data-related jobs is rising by the day. Engineers who work with data aren't exempt from this rule. Companies are constantly on the lookout for qualified Data platform engineers that can deal with large volumes of complex data to provide relevant business insights. Data platform engineers' income potential has also improved as a result of the work requiring a high level of Big Data experience and ability.

What are the roles and responsibilities of Data platform engineers?

The major role of a Data platform engineer is to develop and create a reliable infrastructure for converting data into forms that Data Scientists can interpret. In addition to building scalable algorithms to turn semi-structured and unstructured data into useful representations, remote Data platform engineers must be able to recognize trends in large datasets. Raw data is prepared and transformed by Data platform engineers so that it may be used for analytical or operational reasons. Let's look at the duties of remote Data platform engineer jobs now:

  • Create a scalable data architecture that includes data extraction and manipulation.
  • Build a thorough grasp of data platform costs to develop cost-effective and strategic solutions.
  • Create data products and data flows to support the data platform's continuing growth.
  • Participate in data cleansing and data quality projects - Build automated Data platform engineering pipelines
  • Write high-performance, well-styled, validated, and documented code
  • Translate intricate designs into complicated functional and technological requirements.
  • Hadoop, NoSQL, and other technologies are used to store data.
  • Create models and uncover hidden data patterns
  • Data management techniques must be integrated into the organization's present structure.
  • Assist development of a sound infrastructure with third-party integration.
  • To track data, create high-performance and scalable web services.

How to become a Data platform engineer?

With the right combination of skills and experience, you may start or advance your career in Data platform engineering. Data platform engineers often have a bachelor's degree in computer science or a related field. A degree can help you build a solid foundation of knowledge in this continuously changing field. A master's degree can also help you advance your career and open doors to higher-paying positions.

Data platform engineers are often educated in computer science, engineering, applied mathematics, or a related IT field. Because the work requires a high degree of technical knowledge, prospective Data platform engineers may find that a boot camp or certification is insufficient.

You'll need knowledge of SQL database design and programming abilities in a range of languages, including Python and Java. If you already have a background in IT or a related field like mathematics or analytics, a boot camp or certification might help you create a CV for remote Data platform engineering jobs.

If you don't have any prior experience with technology or IT, you may need to participate in a more intense program to demonstrate your understanding. If you don't already have one, you may need to enroll in an undergraduate program. If you have an undergraduate degree but it isn't in a relevant field, keep looking at master's degrees in data analytics and Data platform engineering.

You'll have a better sense of how your expertise fits into that function if you spend some time going through job advertisements to see what companies are searching for.

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Skills required to become a Data platform engineer

1. Hadoop and Spark

The Apache Hadoop software library is a platform that enables the distributed processing of enormous data volumes across clusters of devices using fundamental programming principles. It's designed to scale from a single server to tens of thousands of devices, each with its own processing and storage capabilities. The framework supports a number of programming languages, including Python, Scala, Java, and R. While Hadoop is the most powerful tool for massive data, it does have certain drawbacks, such as delayed processing and a high degree of coding. Apache Spark is a data processing engine that supports stream processing, or data input and output in real-time. It's a lot like Hadoop in that it does a lot of the same things.

2. C++

C++ is a relatively basic yet powerful programming language for quickly computing big data sets when you don't have a preset algorithm. It's the only programming language capable of processing more than 1GB of data in a single second. You may also apply real-time predictive analytics to retrain the data while keeping the system of record constant.

3. Data Warehousing

A data warehouse is a relational database that can be queried and analyzed to find information. Its purpose is to provide you with a long-term perspective of data through time. A database, on the other hand, refreshes real-time data on a regular basis. Data platform engineers must be familiar with the most prominent data warehousing solutions, such as Amazon Web Services and Amazon Redshift. AWS is a necessity for practically all remote Data platform engineer jobs.

4. Azure

Azure is a Microsoft cloud platform that enables Data platform engineers to build large-scale data analytics applications. It has an easy-to-deploy integrated analytics solution that makes supporting applications and servers quite systematic.The bundle includes pre-built services for everything from data storage to advanced machine learning. Because Azure is so popular, some Data platform engineers have chosen to specialize in it.

5. SQL and NoSQL

For designing and managing relational database systems, the SQL programming language is the industry standard (tables that consist of rows and columns). Depending on their data types, such as a graph or a text, non-tabular NoSQL databases come in a variety of forms and sizes. Data platform engineers must be familiar with database management systems (DBMS), which is a software program that provides an interface to databases for information storage and retrieval.

6. ETL (Extract, Transfer, Load)

The process of taking data from a source, turning it into a format that can be examined, and storing it in a data warehouse is known as ETL (Extract, Transfer, Load). This approach uses batch processing to aid users in assessing data relevant to a specific business situation. The ETL gathers data from various sources, applies business rules to it, and then puts the transformed data into a database or business intelligence platform where it can be accessed and used by everyone in the organization.

Interested in remote Data Platform Engineer jobs?

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How to get remote Data platform engineer jobs?

Working as a programmer may be quite satisfying. However, a solid grasp of programming languages is required. It is suggested that you practice until you achieve perfection. Furthermore, having a product vision is necessary for being in sync with the team. Collaboration with team members and work prioritization according to the long-term goal is aided by good communication skills.

Turing has made things a bit easier for you in your hunt for remote Data platform engineering jobs. Turing has the greatest remote Data platform engineer jobs that can help you advance in your career as a Data platform engineer. Get full-time, long-term remote Data platform engineer jobs with greater income and career progression by joining a network of the world's greatest developers.

Why become a Data platform engineer at Turing?

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

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

Join a worldwide community of elite software developers.

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.

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

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

How much does Turing pay their Data platform engineer?

Turing can assist you in recommending a salary range that will allow you to settle on a lucrative and long-term position. The majority of our recommendations are based on market circumstances and our clients' needs. Because Turing believes in providing the best suitable opportunities to people. As a result, each Data platform engineer is free to choose their own price range based on their talents and experience.

Frequently Asked Questions

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.

After uploading your resume, you will have to go through the three tests -- seniority assessment, tech stack test, and live coding challenge. Once you clear these tests, you are eligible to apply to a wide range of jobs available based on your skills.

No, you don't need to pay any taxes in the U.S. However, you might need to pay taxes according to your country’s tax laws. Also, your bank might charge you a small amount as a transaction fee.

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.

Communication is crucial for success while working with American clients. We prefer candidates with a B1 level of English i.e. those who have the necessary fluency to communicate without effort with our clients and native speakers.

Currently, we have openings only for the developers because of the volume of job demands from our clients. But in the future, we might expand to other roles too. Do check out our careers page periodically to see if we could offer a position that suits your skills and experience.

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.

No, the service is absolutely free for software developers who sign up.

Ideally, a remote developer needs to have at least 3 years of relevant experience to get hired by Turing, but at the same time, we don't say no to exceptional developers. Take our test to find out if we could offer something exciting for you.

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Leadership

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

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Senior Backend Engineer

Before you read on, take a look around you. Everything you see has been shipped, often multiple times, before reaching its destination. Global e-commerce sales are expected to total $5.5 trillion worldwide in 2022 and continue growing over the next few years. Here at Shippo, we are the shipping layer of the internet, and we consider ourselves to be one of the core building blocks of e-commerce.

Our mission is to make merchants successful through world class shipping. With our products and solutions, we level the playing field by providing our customers with best-in-class solutions that otherwise wouldn’t be available to them. Through our e-commerce businesses, marketplaces, and platforms are able to connect to shipping carriers around the world from one API and dashboard. We provide our customers with the most competitive shipping rates, print labels, automated international documents, shipment tracking, facilitate the returns process and more.

About the Role

We are looking for a Senior Backend Engineer to join our Carriers Capabilities Team! Businesses, partners, customers, and users worldwide rely on our integration to a global network of carriers to streamline their fulfillment workflow. You can look forward to expanding our Shipping Carrier Library for both domestic and international shipments. The Carrier Capabilities Team is responsible for developing new integrations with carriers, maintaining them, building infrastructure and maintaining current services. As a Senior Engineer, you will provide experience and oversight in technical definitions, and coding for your team.

 

Job Responsibilities:


  • Design, implement, test, and deploy software services with high SLAs that can handle millions of requests a day
  • Ensure scalability and maintainability through microservices adoption, decoupling of concerns from the data model, queuing of jobs, application layering and container-based software distribution.
  • Continue to build out and enhance our CI/CD pipeline for smooth and safe production releases via automated testing and verification.
  • Verify and ensure performance and correctness of systems in response time and throughput.
  • Architect systems and refactor existing systems for optimal performance and reuse
  • Participate in peer reviews, testing and in design reviews for new features, products, and systems
  • Collaborate with business teams and provide early input to new product ideas and functionality
  • Define, implement, and monitor operational metrics to ensure performance and quality.
  • Work with a sense of urgency and iterate quickly in an agile process.
  • Mentor more junior engineers on engineering best practices.
  • Exceptional problem solving skills: demonstrated ability to understand business challenges and translate those into technical solutions.
  • Being on team on-call rotation and able to respond quickly to system incidents


Job Requirements:


  • 7+ years of experience in software development
  • Coding experience in server-side programming languages (e.g. Python, Go, Java, Ruby) as well as database languages (SQL) in production at scale
  • Experience consuming APIs (client) and processing millions of integrations per second
  • Experience working with server-side frameworks (e.g. Django, FastAPI, .NET, Spring, Rails, Phoenix)
  • Strong interpersonal skills and the ability to work with all levels of the organization.
  • Past experience and success building and supporting scalable APIs, services, or applications
  • Solid understanding of object-oriented programming and familiarity with various design and architectural patterns.
  • Exceptional verbal, written, and interpersonal communication skills. You are adept at communicating relevant information clearly and concisely.
  • Deep understanding of customer needs and passion for customer success.
  • Ability to look ahead to identify opportunities, foster a culture of innovation, and build for scale.
  • Exhibit core behaviors focused on craftsmanship, continuous improvement, and team success
  • BS or MS degree in Computer Science or equivalent experience

Bonus


  • Experience with Integration Patterns Concepts like messaging, routing, translator.
  • Experience working with Enterprise Integration Frameworks (e.g. Apache Camel, Spring Integration) or Data Integration Framework (e.g. Prefect, Sprint Data Streams)
  • Experience with workflow orchestration tools (e.g. Temporal, Kestra, Prefect)
  • Experience using Python and/or Golang in production at scale
  • Interest and experience in performance tuning, concurrency, security, data pipelines, and web servers
  • Familiarity with microservices architectures
  • Experience integrating with APIs that use REST, SOAP, gRPC and other technologies
  • Experience with Django and/or FastAPI
  • Prior experience working or interacting with shipping and/or postal carriers
  • Experience with messaging systems such as NSQ, Kafka, SQS and Celery
  • Experience with DevOps tooling such as Docker, Terraform, Kubernetes, CircleCI, GitHub Actions, ArgoCD, New Relic, PagerDuty, etc
  • Experience with AWS/Cloud services such as EC2, S3, DynamoDB, Lambda, Route 53, Cloud Formation, Cloudflare, Elastic Beanstalk, IAM, etc.

Offer Details

  • Full-time Contractor (No benefits)
  • Remote only, full-time dedication (40 hours/week)
  • Required 5 hours overlap with EST (Eastern Standard Time)
  • Competitive compensation package.
  • Opportunities for professional growth and career development.
  • Dynamic and inclusive work environment focused on innovation and teamwork
Software
251-10K employees
PythonDjangoDynamoDB+ 3
briefcase
Engineering Researcher UG/Master’s/PhD

About Us

Turing is one of the world’s fastest-growing AI companies, pushing the boundaries of AI-assisted software development. Our mission is to empower the next generation of AI systems to reason about and work with real-world software repositories. You’ll be working at the intersection of software engineering, open-source ecosystems, and frontier AI.

Role Overview — What Does a Typical Day Look Like?

You’ll work alongside top AI researchers and domain experts shaping foundational LLMs at leading AI labs to:

  • Design and solve high-quality engineering problems that push the limits of model reasoning—spanning undergraduate through PhD-level topics.
  • Analyze and evaluate model-generated solutions using a structured evaluation and ranking framework.
  • Identify conceptual gaps, edge cases, and model blind spots—helping define new benchmarks for engineering reasoning.
  • Contribute insights that shape model fine-tuning and frontier AI research

Required Skills & Experience

  • Strong academic background in Engineering disciplines (Computer Science, Electrical, Mechanical, Chemical, Civil, Biotechnology, Robotics, or related fields)
  • Open to talent at all education levels — UG, Master’s, and PhD
  • Deep problem-solving skills and a structured, analytical mindset.
  • Strong communication skills to collaborate with technical researchers.
  • Interest in LLMs and how they work is a plus!

Engagement Details

  • Commitment: Work as an expert gig worker with flexible engagement; minimum 10 hrs/week and up to 40 hrs/week (partial PST overlap required)
  • Duration: 1 month with potential extensions based on performance and fit
-
1-10 employees
Growth EngineeringRoboticsElectronic Engineering and Telecommunications
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