Data Engineer Job Description Sample

A data engineer is one who develops, constructs, tests and maintains architectures such as databases and large scale processing systems. The specific tasks handled by data engineers may include building data pipelines, managing platforms and structuring data for use in analytics applications. These professionals are usually expected to have a strong knowledge of platforms, programming and scripting languages and algorithms. Basically, they are required to create the “big data” infrastructure that caters to the analytics needs of Data Scientists.

(This is a sample data engineer Job Description template which you can modify and use for posting on career portals.)

Job brief

We are currently hiring data engineers with X years of experience (mention the number of years as per the requirements of your organisation) in the below mentioned Data Engineering skills.

(Provide a brief intro on your firm, the Data Engineering skill set needed, and the prospects for growth one can expect working as a data engineer for your company.)

Data Engineer - Responsibilities and Deliverables

• Design, implement, and support key datasets so as to provide swift inputs to business information as per the requirements of stakeholders using data stores like Redshift, Postgress etc.
• Automate data pipelines using Linux
• Come up with ideas to convert data into actionable information
• Prepare and ensure adherence to data governance policy
• Use SQL skills to integrate data from a variety of resources
• Design and maintain new and existing (Extract, Transform and Load) solutions
• Design and code using Python, Ruby, Java, C/C++, etc
• Use REST and WSDL services to update data

(Add more duties according to the needs of your organization)

Education and training required to become a Data Engineer

Minimum requirements include a bachelor’s degree in Computer Science, Mathematics, Engineering, or related area.  Experienced candidates with around two to three years work experience as a database engineering support worker or administrator are usually preferred. Employers generally look for candidates with strong skills in MySQL databases and Microsoft SQL., complex data sets, Microsoft Excel, and internet technologies like SaaS.

Required skills

• Strong computer skills
• Ability to develop databases using SSIS, T-SQL, MSSQL and MySQL
• Capacity to manage ETL pipeline and data warehouse
• Confidence in tools like MySQL
• Should be adept in skills like Python, Shell, Java and PHP
• Knowledge of data modeling
• Skill in query performance tuning on various platforms

Personal skills

• Excellent communication skills (key for managerial positions)
• Should be self-motivated
• Strong Interpersonal skills
• Exceptional analytical skills
• Passion for creative thinking
• Ability to be self-motivated
• Ability to meet deadlines and multitask
• Willingness to be a great team player (Should be approachable)

Data Engineer Salary

According to payscale.com, Data Engineers are earning an average salary of $89,771 annually. The salary lies in the range of $62,972 to $140,922.

The good

• Plenty of opportunities (the use of Big Data Analytics has become crucial for beating the competition these days)
• Soaring demand (estimates reveal there will be a 50 - 60% shortage by 2018)
• Many businesses are joining the bandwagon of implementing Big Data Analytics
• Great potential for career growth (the shortage in talent translates to a quicker climb up the career ladder)
• Excellent work life balance
• Abundance of online training options (makes your career switchover easier)
• High paying career (attractive salary for professionals with the right skills)
• High job satisfaction (especially if you like playing around with data)

The bad

• Stress (you may be expected to work long hours in response to looming deadlines)
• Challenging (a lot of time and effort is required to learn various Data Engineering tools)
• You are expected to be good at both programming and Mathematics
• There’s always the risk of making a wrong career move (Not suitable for those who lack passion for data exploration)

Work conditions

As a beginner in the industry, you will be required to put in extra time to deal with the ambiguity and learn various frameworks like Apache Hadoop, Spark etc. Once you are familiar these, you will find things more comfortable. Yet, there is always the need to learn new Data Analysis technologies and tools. Usually, it is a 9-6 job, but you may have to work extra hours or weekends to meet deadlines.

Career outlook

Opportunities are plenty and there is high demand for those well-versed in data engineering. Apart from the tech sector, data engineers are also employed in marketing, healthcare, government, education and financial services. Today, big data is everywhere from Smartphones, automobiles, to even household appliances. More and more companies are looking forward to hiring skilled people who can create the “big data” infrastructure required for analytics. We can expect Data Engineering to expand and flourish as a field in the near future. It goes without saying that aspiring Data Engineers can look forward to a rewarding career with exceptional salary.