Recruit Data Analytics/Operations Engineers
In today’s business world, data plays a crucial role in decision-making processes such as selecting new product lines, entering into new market segments, pursuing investments, and identifying potential or existing customers to target. Moreover, data can help identify weaknesses and other problems that require attention within an organisation.
As a data analyst, it is essential to provide numerical values to key business processes to review and compare performance over a period. However, a data analyst’s tasks go beyond number-crunching; they should also comprehend how data can help organisations make sound decisions.
What prospects are available in Data Analytics/Operations Engineering?
Undoubtedly, companies are shifting towards the digital world, creating a colossal potential for growth. What is driving this significant expansion? Without question, data is being considered the new source of energy and big data analytics is enabling organisations to make better-informed decisions and deliver top-notch products and services. To demonstrate companies’ seriousness about big data analytics, consider the global big data analytics market that was worth USD 37.34 billion in 2018 and is expected to develop at a Compound Annual Growth Rate (CAGR) of 12.3%, achieving USD 105.08 billion by 2027. These figures highlight the massive potential that big data analytics holds for the future.
Operations engineers have multiple employment options available to them, as their skills are applicable in various fields. For instance, they may have to manage various equipment types in the construction sector. Operations engineers may also serve as cost estimators, advisors, and distribution managers in local government, nonprofit organisations, and large corporations alike.
If you are interested in learning more about Data Analytics and Operations Development, then this is the article for you.
What are the tasks and responsibilities of a Data Analytics/Operations engineer?
The primary responsibility of a Data Analyst is to gather, organise, and interpret data to provide valuable insights. According to Stephanie Pham, an analyst at Porter Novelli, Data Analysts’ tasks differ based on the kind of data they are working with (such as sales, social media or inventory) and the client’s project. Data Analysts work in a variety of industries, including healthcare, retail, and fast-food chains. Companies seeking to gain a more in-depth understanding of their customers or users may benefit from the expertise of Data Analysts, who can participate in any phase of the process. Moreover, if a Data Analyst works remotely, they might be required to provide guidelines on how to use their data collection system.
The answer to the question “What does a data analyst do?” can vary depending on the particular organisation’s needs and the extent to which data-driven decisions are in use. However, a data analyst is generally accountable for the following tasks:
- Establishing and maintaining data systems and databases, including fixing coding errors and other data-related issues.
- Collected from primary and secondary sources, data is arranged in a manner that can be interpreted by both humans and machines.
- Statistical analysis is performed on data sets, focusing on identifying trends and patterns that can be used for diagnostic and predictive analytics.
- Evidencing the significance of their operations concerning regional, national, and global trends that impact their business and sector.
- Generating executive reports that utilise relevant data to efficiently communicate trends, patterns, and forecasts.
- Thorough examination of existing processes helps detect potential areas for improvement. Collaborating with programmers, engineers, and organisational leaders, we will propose system upgrades to facilitate these enhancements. Furthermore, we will establish data governance regulations to ensure all stakeholders are responsible for maintaining the system’s integrity.
- As an Operations Engineer, I am accountable for ensuring a company’s operations, including manufacturing and shipping, are executed in an efficient and effective manner to accomplish both production and management objectives.
- Engineers are assigned with the responsibility of performing repairs and upgrades on equipment promptly and effectively. Additionally, they offer guidance to other department heads to optimise the efficiency of their operational systems.
How Can I Secure Employment as a Data Analytics/Operations Engineer?
Data analytics present manifold opportunities across various industries, giving individuals various paths to enter this highly sought-after field. Whether you are embarking on your professional journey or shifting to a new domain, several techniques can aid you in procuring a data analyst position. To commence your career in this thriving sector, consider the following steps:
- For those who are new to the field of data analysis, it is crucial to acquire a comprehensive understanding of the fundamentals. Doing so can not only aid you in determining if this is the appropriate career choice for you, but also equip you with the requisite skills to thrive in the job market.
- Generally, to obtain a remote data analytics job, specialised technical skills are prerequisite. To improve your chances of being recruited, it is essential to acquaint yourself with the programming languages and data visualisation tools specified in job advertisements for the role that you desire. This can be accomplished through courses or by earning a degree or professional certification. Moreover, self-study and independent research can also be an effective method of acquiring the required expertise and proficiencies.
- Engaging in practical experience is one of the most efficient methods of acquiring proficiency in extracting value from data. You can enrol in academic programs or attend seminars that offer hands-on opportunities with actual projects and data sets. Additionally, you can devise your own projects by merging publicly available data sets to gain valuable insight into the usefulness of data.
Now, let’s discuss the competencies you must attain to become a proficient Data Analytics/Operations Engineer:
Requirements for Becoming a Data Analytics/Operations Engineer
Data Analytics/Operations Engineers must exhibit robust deductive reasoning, analytical thinking, problem-solving, and exceptional written and verbal communication abilities. If seeking a vocation in this domain, the first step is to cultivate these fundamental competencies that can be utilised to obtain a lucrative post as a Data Analyst. Here are some crucial factors to bear in mind:
Database Management SoftwareEvery data analyst should possess Microsoft Excel and Structured Query Language (SQL) in their arsenal. While Excel is commonly used in numerous sectors, SQL is preferable for bigger data sets and is often deemed a crucial tool for data analysis.
Computer Programming LanguagesAcquiring proficiency in a statistical programming language, such as Python or R, permits you to process and analyse vast quantities of data and solve complex equations. Python and R are two of the most frequently used programming languages. However, it may be advantageous to research multiple job advertisements to determine which language is most suitable for your company’s developmental needs.
Data VisualisationBeing able to communicate findings effectively to peers, managers, and stakeholders is critical for a successful data analyst. Representing data through charts, graphs, and other visualisations using programs like Tableau, Jupyter Notebook, and Excel can help them better understand the work at hand. Having a fundamental understanding of different data tools and their capabilities is crucial in improving overall business performance. Additionally, data analysts need a sound foundation in statistics and arithmetic to make informed decisions on which tools to use for solving specific problems, identifying data errors, and accurately interpreting outcomes. Furthermore, they should possess the ability to provide engineering support for designing, constructing, operating, and maintaining equipment, processes, or facilities.
Where to Find Remote Data Analytics/Operations Engineer Jobs?
Becoming a Data Analytics/Operations Engineer is one of the most coveted professions today. To secure a job in this field, an individual must possess specific educational qualifications, technical capabilities, and relevant experience. Moreover, they must demonstrate consistency, a comprehensive understanding of programming languages, and a daily routine 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 excel in your Data Analytics/Operations Engineer career. Join a diversified global network of developers and explore full-time remote programming jobs that can help you achieve your professional aspirations. With Works, you can access the knowledge and skills essential to take your career to the next level.
Description of the Job
- Promote the use of a DataOps methodology to the delivery process for automating data provisioning, testing, and monitoring.
- Raise deployment frequency to reduce development cycles and cater to data analytics demands at the earliest possible.
- Work with data architects to develop and enhance a data pipeline for data solutions, including data science products.
- Ensure that the data pipelines are scalable and have high performance.
- Include DataOps and automation projects for production-ready solutions.
- Integrate agile working practices into the delivery process through the use of the DABL framework.
- Collaborate with cross-functional teams to establish a shared DataOps framework for continual delivery and quality assurance.
- Stay abreast of the latest technological advancements, new opportunities, and industry trends to accurately evaluate the impact of services.
- Bachelor’s or master’s degree in engineering or computer science (or equivalent experience)
- With expertise in constructing and managing data technology platforms, I possess over three years of experience in data and analytics. Exceptions may be made for exceptionally skilled developers.
- Proficient in at least one programming language, such as Python, Java, Scala, C++, C#, and others, with hands-on experience in software development and coding.
- Familiarity with microservices and REST API endpoints.
- Thorough comprehension of relational databases, in particular, SQL.
- Proficient in machine learning deployment and operations.
- Familiarity with queuing systems and distributed systems.
- Thorough comprehension of software development best practices.
- Prior experience designing and managing high-performance scalable systems and multi-threaded applications is mandatory.
- Thorough understanding of business intelligence and data warehouse methodologies.
- Proficient in tools including Apache Spark, the ELK stack, Apache Airflow, the Hadoop Ecosystem, Apache Kafka, and Amazon Redshift.
- Fluency in English is necessary for effective communication.
- To work effectively, the candidate must be able to work full-time (40 hours per week) with a 4-hour overlap with US time zones.
- Comprehension of machine learning methods, optimization algorithms, and data mining.
- Comprehension of large-scale distributed systems, such as Hadoop and Spark.
- Familiarity with GCP and AWS can be advantageous.
- Capability to deliver intricate technological concepts to both technical and non-technical stakeholders.
- Exceptional comprehension of the Agile development process.
- Outstanding technical, analytical, and problem-solving capabilities.