Remote data analytics/operations engineer jobs
We, at Turing, are looking for talented remote data analytics/operations engineers who will build assembly lines to develop a data and analytic product in order to bring robust, efficient, and integrated data models. Here's the best chance to collaborate with top industry leaders while working with top Silicon Valley companies.
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Job description
Job responsibilities
- Promote DataOps approach to delivery process to automate data provisioning, testing, and monitoring
- Increase deployment frequency to shorten development cycles and quickly meet the data analytics needs
- Collaborate with data architects to build a data pipeline and optimize it for data solutions including data science products
- Ensure the data pipelines are scalable and highly performant
- Make sure to implement DataOps and automation initiatives for solutions deployed in production
- Implement agile methodologies of working into the delivery process through the use of the DABL framework
- Collaborate with cross-functional teams to drive a common DataOps framework for continuous delivery and quality attainment
- Keep abreast with the latest technology approaches, new opportunities, and industry developments to get the accurate impact of services
Minimum requirements
- Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
- 3+ years of experience with data & analytics with grip over emerging data technology platforms and management (rare exceptions for highly skilled developers)
- Experience in development and coding with one or more programming languages including Python, Java, Scala, C++, C#, etc.
- Experience with microservices and REST API end-points
- Strong knowledge of relational databases, including SQL
- Working experience with ML deployment and operations
- Understanding of queuing systems and distributed systems
- Sound knowledge of software development best practices
- Prior experience in engineering and maintaining high-performance scalable systems and multi-threaded programs
- Solid understanding of BI and data warehousing methods
- Proficient in tools such as Apache Spark, ELK stack, Apache Airflow, Hadoop Ecosystem, Apache Kafka, or Amazon Redshift.
- Fluent in English to communicate effectively
- Ability to work full-time (40 hours/week) with a 4 hour overlap with US time zones
Preferred skills
- Understanding of ML algorithms, algorithmic foundations of optimization and data mining
- Knowledge of large-scale distributed systems like Hadoop and Spark
- Knowledge of GCP and AWS are a plus
- Ability to explain difficult technical topics to technical/non-technical stakeholders
- Excellent knowledge of the Agile development process
- Great technical, analytical and problem-solving skills
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How to Become a Data Analytics/Operations engineer?
Businesses across all industries are increasingly turning to data to help them make critical business decisions including which new products to develop, which new markets to enter, which new investments to make, and which new (or existing) clientele to target. They also use data to identify inefficiencies and other issues in the company that need to be addressed.
In these organisations, the data analyst's role is to give these key business processes a numerical value so that performance can be assessed and compared across time. A data analyst's job is more than just looking at numbers; they must also know how to use data to assist a company in making better decisions.
What is the scope in Data Analytics/Operations engineering?
There's no denying that businesses are going digital and that there's plenty of space for growth. And what's driving this growth? Without a doubt, its data is now considered the new oil. In recent years, big data has helped organizations make better-informed decisions and offer best-in-class goods and services that have become generally recognized. Consider the following numbers if you're not sure how serious businesses are about big data analytics: The global big data analytics market, which was worth USD 37.34 billion in 2018, is expected to grow at a CAGR of 12.3% from 2019 to 2027, reaching USD 105.08 billion. It's clear to understand how big data analytics will flourish in the future, especially with such high values.
On the other hand, Operations engineers can find work in a variety of industries. They can work in the construction industry, with responsibilities centered primarily on equipment. Because their talents are transferrable to a variety of industries, operations engineers can also work as cost estimators, consultants, and distribution managers. Local governments, institutions, and large enterprises can all use them.
Looking to know more about Data Analytics/Operations development? Then this article is for you.
What are the roles and responsibilities of a Data Analytics/Operations engineer?
A data analyst's job is to acquire and gather data, organize it, and draw usable conclusions from it. "Data analysts' responsibilities vary depending on the type of data they're dealing with (sales, social media, inventory, etc.) as well as the specific client project," says Stephanie Pham, an analyst at Porter Novelli. Data analysts are employed in a wide range of industries, including healthcare, retail, and fast-food restaurants. Employers who want to understand more about their customers or end-users may profit from the insights provided by data analysts. Analysts can take part in any step of the investigation. If you work as a data analyst remotely, you may be needed to train people on how to use your data collecting system.
Depending on the type of company and the extent to which data-driven decision-making procedures have been applied, the answer to the question "What does a data analyst do?" will vary. However, the following are the general responsibilities of a data analyst:
- The creation and maintenance of data systems and databases, as well as the correction of coding errors and other data-related issues.
- Data is gathered from primary and secondary sources and structured in a manner that humans and machines can understand.
- Analyzing data sets using statistical approaches, with a focus on trends and patterns that may be beneficial for diagnostic and predictive analytics.
- Demonstrating the significance of their work in the context of local, national, and international trends that impact their organization and industry.
- Creating executive reports that effectively convey trends, patterns, and projections using relevant data.
- In partnership with programmers, engineers, and organizational executives, identifying opportunities for process improvements, advocating system upgrades, and implementing data governance policies.
- An operations engineer's duty is to ensure that a company's operations, such as production and shipping, are running smoothly and meet factory and management requirements.
- These engineers are in charge of any machinery repairs or upgrades, as well as collaborating with other department heads to fine-tune their operating systems.
How to Become a Data Analytics/Operations engineer?
Data analytics employment is available in a wide range of businesses, and there are various methods to break into this in-demand field. Whether you're just starting out in the professional world or moving careers, here are some steps to getting a job as a data analyst. If you're interested in pursuing a career in this in-demand field, here's how to get started.
- If you're new to data analysis, you should start by studying the fundamentals. Gaining a solid understanding of data analytics will assist you in determining whether or not this is the correct vocation for you while also equipping you with marketable skills.
- Obtaining a remote data analytics job typically needs a set of specialised technological skills. Whether you're learning through a degree programme, a professional certificate, or on your own, these are some fundamental skills you'll likely need to get hired. Examine some job advertisements for positions you want to apply for, and focus your studies on the programming languages or visualisation tools that are required.
- Working with data in real-world situations is the most effective way to learn how to extract value from it. Seek out degree programmes or classes that incorporate real-world projects and data sets. You can also develop your own projects using a variety of freely available public data sets.
Now, let’s dive further into the skills you need to master to become a proficient Data Analytics/Operations engineer:
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Skills required to become a Data Analytics/Operations engineer
Data Analytics/Operations engineer must be proficient with deductive reasoning, analytical thinking, problem solving, and Good Written and Verbal Communication. The first step is to gain the fundamental abilities that will assist you in landing a high-paying Data analyst position. Let's look at some of the things you should be aware of:
1. Database software
Microsoft Excel and SQL should be part of any data analyst's toolkit. While Excel is widely used in a variety of industries, SQL can handle larger data sets and is often considered a requirement for data analysis.
2. Programming languages
If you learn a statistical programming language like Python or R, you'll be able to manage large amounts of data and solve difficult equations. Despite the fact that Python and R are two of the most popular programming languages, it's a good idea to look at numerous job descriptions for a position you're interested in to determine which language will be most useful in your organizational growth.
3. Data visualisation
To be successful as a data analyst, you must be able to communicate your findings in a clear and convincing manner. Knowing how to present data in charts and graphs can help your coworkers, bosses, and stakeholders comprehend what you're up to. Tableau, Jupyter Notebook, and Excel are some of the programmes used to make visuals.
Understanding the principles of what data tools do will substantially benefit you in your work. A strong understanding of statistics and math will enable you in selecting which tools to use to solve a specific problem, spotting data errors, and comprehending the results.
They should also be able to give engineering support for equipment, process, or facility planning, development, operation, and maintenance.
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How to get remote Data Analytics/Operations engineer jobs?
Data Analytics/Operations Engineer is one of the most in-demand jobs. Obtaining a remote work is a detail-oriented profession that requires education, skills, and experience. To operate as a remote Data Analytics/Operations engineer, you'll need regular practise, a good understanding of programming languages, and a daily routine.
Turing provides the best remote Data Analytics/Operations engineer jobs available to help you achieve your career objectives. We give you the tools you need to study, grow, and advance in your Data Analytics/Operations Engineer profession. Join a global network of like-minded developers and obtain full-time remote development opportunities to further your career.
Why become a Data Analytics/Operations engineer at Turing?
Elite US jobs
Long-term opportunities to work for amazing, mission-driven US 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 US firms from the comfort of your home.
Great compensation
Working with top US corporations, Turing developers make more than the standard market pay in most nations.
How much does Turing pay their Data Analytics/Operations engineer?
Turing gives each Data Analytics/Operations engineer complete control over their price. Turing has suggested a salary that we believe will help you secure a stable long-term job. We carefully analyze your abilities, market conditions, and consumer demand before making a compensation recommendation.
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