Sr Scala Data Engineer

As a Senior Scala Data Engineer at The Hartford, you'll be responsible for estimating and designing components, building and testing high-quality code, and collaborating with your team to define requirements. You'll contribute to various practices including design, testing, and peer reviews, while continuously looking for opportunities to enhance our software delivery. Communication and teamwork are vital as you work closely with both business stakeholders and the delivery team to keep projects on track.

To apply for the Senior Scala Data Engineer role at The Hartford, you should possess a Bachelor's degree or equivalent experience in a related field and have a minimum of 5 years of software development experience. Specifically, at least 2 years of hands-on experience in Scala programming is required, alongside familiarity with data transformation and aggregation using Spark. It's also essential to have experience with AWS technologies for this position.

The hybrid work arrangement for the Senior Scala Data Engineer role at The Hartford requires employees to work from the office three days a week (Tuesday through Thursday) while allowing flexibility for remote work on the remaining days. This model is designed to encourage collaboration with team members while also providing the benefits of a remote work environment.

Senior Scala Data Engineers at The Hartford use a variety of tools and technologies, including Scala for functional and object-oriented programming, AWS services such as S3 and EMR for cloud computing, and various big data technologies like Hadoop and Spark. Familiarity with testing frameworks and code quality tools is also important for ensuring high standards of software development and delivery.

The compensation range for the Senior Scala Data Engineer position at The Hartford typically falls between $113,360 and $170,040, depending on various factors such as experience and performance. In addition to the base pay, The Hartford offers a comprehensive total compensation package that may include bonuses, long-term incentives, and additional recognition rewards.

When answering this question, focus on specific projects where you've utilized Scala, particularly for data transformation and processing. Highlight your familiarity with both object-oriented and functional programming aspects of Scala and how they've helped achieve project goals.

Discuss best practices such as adhering to coding conventions, writing unit tests, conducting code reviews, and using appropriate design patterns. Emphasize the importance of code maintainability and readability in your projects.

Highlight your experience with version control systems like Git. Discuss workflows you’ve used, such as feature branching or pull requests, and how these approaches help ensure code quality and team collaboration.

Share your experience working with AWS services like S3 and EMR. Explain how you've utilized these services for data storage, processing, and analysis within your Scala projects, underscoring their importance in cloud-based data engineering.

Discuss methods such as logging, using Spark UI for monitoring, and writing unit tests to catch issues early. Share specific examples of challenges you faced and how you resolved them effectively.

Emphasize the importance of clear communication. Discuss your approach to understanding requirements, translating technical concepts into layman's terms, and ensuring all parties are aligned on project goals.

Provide a concise story detailing the problem, your analysis, the solution you implemented, and the results. Focus on your critical thinking skills and your ability to adapt and learn from the experience.

Share how you stay updated with industry trends and new technologies, such as attending workshops, obtaining certifications, or participating in online courses. Stress the significance of continuous learning in your growth as a data engineer.

Talk about the importance of peer reviews in maintaining code quality and team collaboration. Provide examples of how you handle feedback constructively and how you give helpful suggestions to others.

Reflect on current trends and challenges in the field, such as managing big data, ensuring data quality, or keeping up with rapid technological advancements. Discuss how these challenges may be addressed through innovative solutions.