Hire Data Analytics/Operations Engineers
Businesses in all industries are increasingly relying on data to help them make important decisions such as what new products to manufacture, which new markets to enter, which investments to pursue, and which potential (or existing) customers to target. Additionally, data is being used to identify inefficiencies and other issues that need attention within the organisation.
As a data analyst, it is essential to provide numerical values to core business processes in order to review and compare performance over time. However, the duties of a data analyst go beyond simply crunching numbers; it is also necessary to understand how to use data to help organisations make effective decisions.
What are the opportunities in Data Analytics/Operations Engineering?
It is clear that companies are transitioning to the digital world and there is plenty of potential for growth. So, what is driving such expansion? Without a doubt, data is becoming the new fuel and big data analytics is enabling organisations to make better-informed decisions and deliver top-notch products and services. To demonstrate how seriously companies are taking big data analytics, consider the following figures: According to industry estimates, the global big data analytics market was worth USD 37.34 billion in 2018 and is projected to grow at a Compound Annual Growth Rate (CAGR) of 12.3%, reaching USD 105.08 billion by 2027. These figures serve to highlight the immense potential that big data analytics holds for the future.
Operations engineers have a variety of career options available to them, as their skills can be applied in many different areas. In the construction sector, for example, their tasks may involve the operation of various types of equipment. Additionally, operations engineers may be employed as cost estimators, consultants, and distribution managers in both local government, nonprofit organisations, and large corporations.
Do you want to learn more about Data Analytics and Operations Development? Then this is the article for you.
What are the duties and obligations of a Data Analytics/Operations engineer?
As a Data Analyst, one’s job is to collect, arrange, and interpret data in order to provide useful insights. Stephanie Pham, an analyst at Porter Novelli, explains that the duties of Data Analysts vary depending on the type of data they are working with (such as sales, social media, or inventory) and the project for the client. Data Analysts are employed in a variety of industries, including healthcare, retail, and fast-food restaurants. Companies that are looking to gain a better understanding of their customers or users could potentially benefit from the expertise of Data Analysts. They can be involved during any stage of the process. Additionally, if a Data Analyst works remotely, they may be expected to provide instruction on how to use their data collection system.
The answer to the question of “What does a data analyst do?” can vary depending on the particular organisation and the extent to which data-driven decisions are used. Generally speaking, however, a data analyst is typically responsible for the following tasks:
- The development and upkeep of data systems and databases, as well as the repair of coding mistakes and other data-related problems.
- Data is collected from primary and secondary sources and organised in a way that people and robots can comprehend.
- Data sets are analysed statistically, with an emphasis on trends and patterns that may be used for diagnostic and predictive analytics.
- demonstrating the importance of their work in relation to local, national, and worldwide trends affecting their business and industry.
- Creating executive reports that use pertinent data to effectively express trends, patterns, and predictions.
- By conducting thorough analysis of existing processes, we can identify areas of potential improvement. We will then work closely with programmers, engineers, and organisational leaders to promote system upgrades that can help to advance these improvements. Finally, we will create data governance rules to ensure that all stakeholders are held accountable in order to maintain the integrity of the system.
- As an operations engineer, it is my responsibility to ensure that a company’s operations, such as manufacturing and shipping, are carried out in an efficient and effective manner in order to meet both factory and management criteria.
- The engineers are tasked with ensuring that all repairs and improvements to equipment are carried out in a timely and efficient manner, as well as providing consultation to other department heads to help them maximise the efficiency of their operational systems.
How Do I Get a Job as a Data Analytics/Operations Engineer?
Data analytics offer a range of opportunities in multiple industries, giving individuals diverse options for entering this highly sought-after field. Whether you are just beginning your professional career, or transitioning to a new area, there are various methods to finding a job as a data analyst. To start a career in this burgeoning sector, consider the following steps:
- If you are new to the field of data analysis, it is important to gain a comprehensive understanding of the fundamentals. Doing so will not only help you decide if this is the right profession for you, but also give you the necessary skills to be successful in the job market.
- Typically, to secure a position in remote data analytics, a set of specialised technical skills are required. To increase your chances of getting hired, it is important to familiarise yourself with the programming languages and data visualisation tools listed in job postings for the role you are interested in. This can be achieved through taking courses or earning a degree or professional certification. Additionally, self-learning and independent research can also be a great way to gain the necessary knowledge and skills.
- One of the most efficient ways to gain expertise in extracting value from data is to engage in practical experience. Consider enrolling in academic programs or attending seminars that provide hands-on opportunities with real-world projects and data sets. Additionally, by combining publicly available data sets, you can devise your own projects and gain valuable insight into the value of data.
Now, let’s go through the abilities you’ll need to acquire in order to become a competent Data Analytics/Operations engineer:
Qualifications for becoming a Data Analytics/Operations engineer
Data Analytics/Operations Engineers must demonstrate strong deductive reasoning, analytical thinking, problem solving, and excellent written and verbal communication skills. If you are seeking a career in this field, the first step is to develop these core competencies that can be used to attain a lucrative position as a Data Analyst. Here are some important considerations to keep in mind:
database management softwareAny data analyst should have Microsoft Excel and Structured Query Language (SQL) in their toolkit. Excel is widely used in many industries, but SQL is preferred for larger data sets and is often considered essential for data analysis.
Computer programming languagesIf you gain proficiency in a statistical programming language such as Python or R, you will be able to process and analyse large amounts of data and solve complicated equations. Python and R are two of the most commonly used programming languages, but it may be beneficial to research various job postings to determine which language will best suit the developmental needs of your company.
Visualisation of dataIn order to be a successful data analyst, it is essential to be able to effectively communicate results to colleagues, managers, and stakeholders. Presenting data in graphs, charts, and other visualisations using programs such as Tableau, Jupyter Notebook, and Excel can help colleagues, managers, and stakeholders to better understand the work being done. Having a basic understanding of the various data tools and their capabilities is important to improving overall business performance. Furthermore, a strong foundation in statistics and arithmetic is necessary to make informed decisions on which tools to use to solve a particular problem, spot data errors, and properly interpret the results. Additionally, data analysts should possess the ability to offer engineering support for the design, construction, operation, and maintenance of equipment, processes, or facilities.
Where can I find remote Data Analytics/Operations Engineer jobs?
Becoming a Data Analytics/Operations Engineer is one of the most sought-after careers today. Gaining employment in this field requires an individual to possess certain educational qualifications, technical abilities and relevant experience. Furthermore, individuals need to demonstrate regular commitment, a comprehensive understanding of programming languages, and a daily routine in order to be successful in this role.
Works is proud to offer the most comprehensive remote Data Analytics/Operations Engineer positions available, providing you with the necessary resources to develop and succeed in your Data Analytics/Operations Engineer career. Join a diverse global network of developers and discover full-time remote programming jobs that can help you reach your professional ambitions. With Works, you can gain access to the knowledge and skills necessary to take your career to the next level.
Responsibilities at work
- Encourage the use of a DataOps approach to the delivery process in order to automate data provisioning, testing, and monitoring.
- Increase deployment frequency to minimise development cycles and address data analytics demands as soon as possible.
- Collaborate with data architects to create and optimise a data pipeline for data solutions, including data science products.
- Make certain that the data pipelines are scalable and highly performant.
- Make sure you incorporate DataOps and automation projects for production-ready solutions.
- Using the DABL framework, include agile working practices into the delivery process.
- Work with cross-functional teams to develop a common DataOps framework for continuous delivery and quality assurance.
- To accurately assess the effect of services, stay up to date on the newest technological advances, new prospects, and industry trends.
- Engineering or computer science bachelor’s/degree master’s (or equivalent experience)
- I have over three years of experience in data and analytics, with an in-depth understanding of constructing data technology platforms and managing them. Exceptions are made for exceptionally talented developers.
- Experience developing and coding in one or more programming languages, such as Python, Java, Scala, C++, C#, and others.
- Knowledge of microservices and REST API endpoints.
- Solid understanding of relational databases, especially SQL.
- Working knowledge of ML deployment and operations.
- Knowledge of queuing systems and distributed systems.
- Solid understanding of best practices in software development.
- Previous expertise designing and managing high-performance scalable systems and multi-threaded applications is required.
- Solid grasp of business intelligence and data warehouse methodologies.
- Expertise in tools such as Apache Spark, the ELK stack, Apache Airflow, the Hadoop Ecosystem, Apache Kafka, and Amazon Redshift.
- To communicate successfully, you must be fluent in English.
- Work full-time (40 hours a week) with a 4-hour overlap with US time zones.
- Understanding of ML methods, optimisation algorithms, and data mining.
- Understanding of large-scale distributed systems such as Hadoop and Spark.
- Knowledge with GCP and AWS is advantageous.
- Ability to convey complex technological concepts to technical and non-technical stakeholders.
- Outstanding understanding of the Agile development process.
- Excellent technical, analytical, and problem-solving abilities.