Data Infrastructure Engineer Job Description [Updated for 2024]

In the era of big data, the focus on Data Infrastructure Engineers has never been more pronounced.

As technology advances, the demand for skilled professionals who can build, expand, and protect our data infrastructure grows stronger.

But let’s delve deeper: What’s really expected from a data infrastructure engineer?

Whether you are:

• A job seeker trying to understand the core of this role,
• A hiring manager outlining the perfect candidate,
• Or simply fascinated by the complexities of data infrastructure engineering,

You’ve come to the right place.

Today, we present a customizable Data Infrastructure Engineer job description template, designed for easy posting on job boards or career sites.

Let’s dive right into it.

Data Infrastructure Engineer Duties and Responsibilities

Data Infrastructure Engineers are responsible for creating and maintaining the data infrastructure of a company.

They use various tools, programming languages, and data science concepts to ensure the smooth processing and storage of data.

Their duties and responsibilities include:

• Design and build robust, scalable data infrastructure systems
• Ensure the data integrity and security by developing and implementing necessary measures
• Identify and implement the most appropriate data storage solutions
• Work closely with data scientists and analysts to understand their data requirements
• Develop and maintain ETL processes to facilitate data movement and processing
• Provide troubleshooting and support for the existing data infrastructure
• Monitor the performance of the data infrastructure and make necessary adjustments
• Stay updated with the latest industry trends and technologies related to data infrastructure
• Document all procedures and systems related to data infrastructure for future reference and maintenance
• Collaborate with other IT teams to integrate systems and data effectively

 

Data Infrastructure Engineer Job Description Template

Job Brief

We are looking for a skilled Data Infrastructure Engineer to join our team.

This role involves managing and optimizing our data architecture, as well as developing database support tools and methodologies.

Data Infrastructure Engineer responsibilities include ensuring our data systems perform well, securing data, and troubleshooting any issues with the system.

You should also be able to implement strategies to improve system performance and provide end-user training where required.

Our ideal candidate is proficient in data management, possesses a strong command of data warehousing solutions, and is familiar with big data tools and cloud platforms.

 

Responsibilities

• Develop and implement data standards, ensuring data quality and access.
• Design, construct, install, test, and maintain data management systems.
• Ensure all data systems meet company requirements as well as industry practices.
• Develop database design and architecture documentation for management and executive teams.
• Work closely with developers, system analysts, and users to understand data needs.
• Develop strategies for data acquisitions, archive recovery, and implementation of databases.
• Manage and monitor data systems to ensure they meet user needs, are secure, and operate properly.
• Collaborate with data architects to visualise data and create reports.
• Handle capacity planning and forecast for database systems.
• Develop strategies for data acquisitions and integration of new data into company databases.

 

Qualifications

• Proven work experience as a Data Infrastructure Engineer or similar role in Database Administration.
• Experience with database design and data modeling.
• Excellent knowledge of data backup, recovery, security, and integrity.
• Familiarity with database design, documentation, and coding.
• Experience with SQL and/or NoSQL databases.
• Knowledge of big data tools (Hadoop, Spark) and data pipeline tools (Airflow, NiFi).
• Experience with cloud services (AWS, Google Cloud, Azure).
• Problem-solving attitude and ability to work in a team environment.
• BS degree in Computer Science or relevant field.

 

Benefits

• 401(k)
• Health insurance
• Dental insurance
• Retirement plan
• Paid time off
• Professional development opportunities

 

Additional Information

• Job Title: Data Infrastructure Engineer
• Work Environment: Office setting with options for remote work. Some travel may be required for team meetings or client consultations.
• Reporting Structure: Reports to the Lead Data Engineer or Data Engineering Manager.
• Salary: Salary is based upon candidate experience and qualifications, as well as market and business considerations.
• Pay Range: $80,000 minimum to $130,000 maximum
• Location: [City, State] (specify the location or indicate if remote)
• Employment Type: Full-time
• Equal Opportunity Statement: We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
• Application Instructions: Please submit your resume and a cover letter outlining your qualifications and experience to [email address or application portal].

 

What Does a Data Infrastructure Engineer Do?

Data Infrastructure Engineers are typically employed by corporations across different industries where they work on developing, constructing, testing, and maintaining architectures such as databases and large-scale processing systems.

They interact closely with Data Scientists and Analysts, ensuring that they have the necessary infrastructure, data, and tools to carry out high-level data analysis.

This often includes the creation of custom software components and analytics applications.

One of their main responsibilities is to design and implement efficient and secure databases and data processes.

This involves ensuring data quality and accessibility, integrating new data management technologies and software engineering tools into existing structures, and improving and maintaining data reliability, efficiency, and quality.

Data Infrastructure Engineers are also responsible for selecting the appropriate storage and processing tools, keeping up with the latest industry trends, and implementing new models and methodologies to improve data consistency and speed up data retrieval.

They are often tasked with ensuring that the data architecture is scalable and can handle large volumes of data while still providing useful insights.

They may also be involved in troubleshooting any issues that arise in the data pipelines and implementing necessary fixes or improvements.

In addition, they may also work on creating data backup and recovery plans to ensure data durability and persistence.

This includes developing and managing company-wide data policies, standards, and procedures.

 

Data Infrastructure Engineer Qualifications and Skills

A proficient Data Infrastructure Engineer should have a blend of technical knowledge, analytical abilities, and soft skills that are crucial for designing, building, and maintaining data infrastructure systems.

These include:

• Strong knowledge of database management systems, data modelling, and ETL (Extract, Transform, Load) principles.
• Proficiency in programming languages such as Python, Java, or SQL that are commonly used in data infrastructure.
• Experience with data warehousing solutions and handling big data technologies like Hadoop, Spark or other distributed computing systems.
• Understanding of cloud-based data solutions and familiarity with platforms like AWS, Google Cloud, or Azure.
• Ability to troubleshoot and resolve data infrastructure related issues, displaying strong problem-solving skills.
• Excellent analytical abilities to understand the organization’s data needs and translate them into technical requirements.
• Strong interpersonal and communication skills to effectively collaborate with other team members including data scientists, analysts, and stakeholders.
• Attention to detail and strong organizational skills to manage and prioritize multiple projects and tasks simultaneously.
• Understanding of data privacy and governance laws, ensuring data infrastructure adheres to necessary compliance and regulations.

 

Data Infrastructure Engineer Experience Requirements

Entry-level candidates for the role of a Data Infrastructure Engineer usually possess a degree in Computer Science, Information Systems, or related fields, and they may have 1 to 2 years of experience in the field of data engineering.

This experience often comes through internships, part-time roles, or graduate programs where they have built and maintained databases, developed data pipelines, or been involved in data warehousing projects.

Candidates with 3 to 5 years of experience are expected to have a more comprehensive understanding of data infrastructure systems.

They usually have hands-on experience in designing, building, and managing data infrastructure systems.

This includes data modeling, designing and implementing ETL pipelines, and working with big data technologies like Hadoop, Spark, and others.

They should also be familiar with various database technologies including SQL and NoSQL databases.

Senior-level Data Infrastructure Engineers, often with more than 5 years of experience, are usually proficient in managing large-scale data infrastructure projects, and they have a deep understanding of data architecture.

They are expected to be competent in using cloud computing platforms like AWS, GCP or Azure, and have experience with data warehousing solutions such as Redshift, BigQuery or Snowflake.

These professionals often have leadership experience and are capable of managing teams, making strategic decisions, and leading large-scale data infrastructure projects to successful completion.

 

Data Infrastructure Engineer Education and Training Requirements

Data Infrastructure Engineers typically require a bachelor’s degree in computer science, software engineering, or a related field.

A strong foundation in data structures, algorithms, and software design is essential.

Familiarity with programming languages such as Java, Python, and C++ is beneficial.

An understanding of database systems and knowledge in SQL is a must.

Experience with big data tools like Hadoop, Hive, or Spark can be an added advantage.

Many positions require Data Infrastructure Engineers to have a master’s degree or higher in data science, information systems, or a related discipline, especially for senior or specialized roles.

Several certifications are available for professionals in this field, such as the Microsoft Certified: Azure Data Engineer Associate or Google Certified Professional Data Engineer.

These credentials can help demonstrate a candidate’s proficiency and commitment to maintaining up-to-date knowledge.

Experience in data warehousing, data architecture, and large-scale data processing is also a valuable addition to formal education.

Ongoing training and education are critical in this rapidly evolving field to stay updated with the latest trends and technologies.

 

Data Infrastructure Engineer Salary Expectations

The average salary for a Data Infrastructure Engineer is approximately $117,706 (USD) per year.

However, the actual earnings can vary widely based on factors such as experience, certifications, the complexity of the infrastructure managed, and the geographical location of the job.

 

Data Infrastructure Engineer Job Description FAQs

What skills does a Data Infrastructure Engineer need?

Data Infrastructure Engineers should have strong programming skills, particularly in languages such as Python, Java, and SQL.

They should also have a deep understanding of data structures, algorithms, and systems architecture.

Experience with big data tools like Hadoop, Spark, or Kafka, as well as cloud platforms like AWS, Google Cloud, or Azure, is essential.

They should also have strong analytical skills and the ability to problem-solve complex issues.

 

Do Data Infrastructure Engineers need a degree?

Most Data Infrastructure Engineers have a degree in Computer Science, Information Technology, or a related field.

While this is not always required, it’s commonly sought by employers.

Many also have postgraduate degrees or certifications in data science, big data, or related specialties.

 

What should you look for in a Data Infrastructure Engineer resume?

When reviewing a Data Infrastructure Engineer’s resume, look for experience in designing, building, and maintaining data infrastructure systems.

They should also have a strong programming background, with proficiency in various languages and tools.

Experience with specific big data tools and cloud platforms, as well as any evidence of problem-solving abilities or innovative thinking, should be considered a plus.

 

What qualities make a good Data Infrastructure Engineer?

A good Data Infrastructure Engineer is highly analytical and detail-oriented.

They need to be able to identify patterns, troubleshoot issues, and come up with effective solutions.

They should also be good communicators, capable of explaining complex systems and concepts to non-technical team members.

They should be comfortable working in a fast-paced environment and be able to manage multiple tasks at once.

 

Is it difficult to hire Data Infrastructure Engineers?

Hiring a Data Infrastructure Engineer can be challenging due to the specialized nature of the role and the high demand for professionals with these skills.

Offering competitive salaries, opportunities for ongoing learning and development, and engaging, innovative projects can make the recruitment process easier.

 

Conclusion

And there you have it.

Today, we’ve unveiled the intriguing world of a data infrastructure engineer.

Surprising, right?

It’s not just about data analysis.

It’s about shaping the future of information, one data point at a time.

Armed with our reliable data infrastructure engineer job description template and real-life examples, you’re ready to take the leap.

But don’t stop at that.

Go beyond with our job description generator. It’s your key to creating precision-targeted listings or refining your resume to flawlessness.

Remember:

Every data point contributes to the larger data landscape.

Let’s construct that future. Together.

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