What does a Data Engineer do?
Data engineers are mainly tasked with transforming data into a format that can be easily analyzed. They do this by developing, maintaining, and testing infrastructures for data generation. Data engineers work closely with data scientists and are largely in charge of architecting solutions for data scientists that enable them to do their jobs.
Data engineers generally have a bachelor's degree in computer science, information technology, or applied math, as well as a few data engineering certifications like IBM Certified Data Engineer or Google's Certified Professional. In addition, data engineers possess a plethora of technical skills and the ability to approach problems in a creative manner.
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Data Engineer Salaries
Average Base Pay
Data Engineer Career Path
Learn how to become a Data Engineer, what skills and education you need to succeed, and what level of pay to expect at each step on your career path.
Average Years of Experience
Data Engineer Insights
“Very much happy to be part of this company where I see great future in my career.”
“This culture made Gensquared a place where I throughly enjoyed my work and looked forward to each day.”
“Big challenging projects of diverse tech stacks to grow and get aware about your career path to follow.”
“Not a great salary and can get complicated if you don't have a client to work with.”
“Good payment for your work and recognises you if you and your work is worth of.”
“Good payment for your work and recognises you if you and your work is worthy of.”
“You are not bound to just certain tasks in a project which is a great learning experience”
“Nothing much to say apart from a little miss of work life balance which is expected in any startup around”
Data Engineer Interviews
Frequently asked questions about the role and responsibilities of data engineers
The typical day of a data engineer involves working with large collections of data, recording and analyzing it, then converting it into easy-to-read reports or presentations. They may also be responsible for creating organized databases with detailed programs to help businesses collect and interpret data.
The best part about being a data engineer is that they're in demand in most industries, as they have the necessary skills to understand large amounts of data. Most data engineers can work a traditional schedule and may have the chance to work remotely.
Working as a data engineer can be challenging, as clients expect them to sift through large amounts of data to identify the most relevant information. A difficult aspect of being a data engineer is that it may be time-consuming and difficult to design systems that capture important data.