Three years of data engineering at Target
This post has long been overdue since I left Target in 2022. As I prepare to embark on my next professional endeavor, I thought it would be great to reminisce about my time at Target. If you have wondered how it is to work as a Data Engineer at one of the largest and most successful retailers in the United States, I hope this post can provide you with some valuable insights. I feel grateful to have started my full-time career as a Data Engineer at Target India which helped me grow both professionally and personally. Reflecting on my journey, first, I have discussed the things that I absolutely loved at the company, and towards the end, I have talked about two principles that guided my growth as a data engineer at Target.
Great culture
Target is a very welcoming company and I felt it right from day one. As a fresher, the onboarding process was a great opportunity to build my network. During the initial weeks, when I was introduced to the tech stack and worked in a team on a project, I got plenty of opportunities to connect with technical subject matter experts (SMEs) and lead data engineers from various teams. This encourages cross-functional team collaboration and new employees get an idea of who to reach out to in case of technical challenges. I was fortunate to work with cross-functional teams, learning from experts across different domains. There were a lot of fun activities as well to foster employee bonding. Afterward, during the team onboarding, a buddy/mentor will be assigned to you who will be there to answer any questions you have regarding what the team does, how the work is done, how to improve technical skills, and much more. Apart from this, mentors suggested ways in which we can best contribute to the team.
Work-life balance
I was impressed with Target’s commitment to fostering a positive work-life balance. And I truly believe Target can easily beat most Fortune companies when it comes to work-life balance. Target understands that life can be unpredictable, and offers a range of programs and benefits to support employees in their personal lives. Especially during the COVID-19 pandemic when most employees worked from home, Target offered mental health resources and established fixed time slots for offsite team meetings ensuring employees stay healthy and have adequate time to take care of themselves and their families during uncertain times. If you’re searching for a company that values your holistic well-being, I feel Target is one of the best options to have. Team members at Target are also very supportive; I never felt overwhelmed with work apart from when I had to deal with fixing occasional issues in data pipelines :)
Immense learning opportunities
Target values professional growth and development and I have had access to an abundance of learning opportunities that have helped me expand my skills and knowledge in data engineering. It is a great place to learn, grow, and create an impact.
Target is a large organization with 1900+ retail stores, and the sheer size of the company and the volume of data it generates means data engineering challenges are imminent. These challenges ultimately provide opportunities to upskill ourselves technically and professionally. Resolving issues in data pipelines also helped me a lot as I gained a deep understanding of the big data platform while reviewing system logs to identify the root cause and fix errors. I can also say, every project that I undertook exposed me to a diverse range of teams and technologies with its unique set of growth opportunities. I was able to build connections with different data product owners, data scientists/analysts, and data platform engineers while working on projects.
Additionally, Target has a culture of continuous improvement and employees have the freedom to identify areas of improvement and drive change. I worked on several tasks that focus just on optimizing and streamlining the existing data processing systems. Employees are also encouraged to create an impact through meaningful contributions at an organizational level. Data engineers are allowed to collaborate with different teams to work on products that have the potential to improve the efficiency of teams. They are even allowed to have a certain amount of duration in each sprint dedicated to working on these kinds of initiatives that go beyond day-to-day responsibilities.
Elevating myself
Target encourages employees to grow in their roles, but ultimately it all depends on us. I feel it is important for us to take ownership of our career paths and look for ways to show our true potential to our employers. That is what makes our jobs interesting and keeps us motivated to do our best work. The two principles that helped me grow in my data engineering career at Target were:
- Taking up challenging projects: I was able to improve a lot technically and professionally by doing this — pushing me out of my comfort zone and helping me to develop new skills and competencies. Reach out to your manager to ask about new projects coming up and show your interest to work on challenging projects — something that involves learning new technology, collaborating with new partners, following unconventional approaches, or anything that has not been done before and has the potential to be helpful to other teams as well.
- Going above and beyond: Obviously, giving 100% to whatever you do is how you build trust with team members and managers. But, it is also necessary to bring out the visionary in you and develop products with future needs in mind. In terms of data processing applications, scalability, modularization, and robustness are the three things we should focus on.
Following these two principles is extremely rewarding. I took up a challenging data migration project which required me to learn new technologies and build an end-to-end data pipeline on an entirely new big data framework. I designed and implemented the data architecture and gave importance to scalability and modularization for future changes to be easily integrated. The data pipeline served as a template, and other data engineers started using it as a reference for the migration of other data pipelines. This project helped me put a strong case forward for my promotion to the Senior Data Engineer role as well.
Technically, I was able to build skills in data modeling, data warehousing, distributed computing using Spark, and ETL development and got to work on big data technologies such as Apache Kafka, Hadoop, Hive, Oozie, and various other internal tools used for data quality, data discovery, data lineage, monitoring, and dashboarding.
Overall, my experience at Target was transformative, and I could not have asked for a better start to my career as a data engineer. I have acquired an invaluable set of skills that will guide me in my future endeavors, and I am excited to take the lessons learned and apply them to my next adventure.
The insights shared in this blog post are based on my personal experiences and observations as a Data Engineer at Target. Opinions might be different for others, and I feel it largely depends on the team you are part of.
