Job summary
Job post source
This job is directly from Target
Job overview
The Data Engineer role at Target involves developing scalable and robust software components to support the company's products, focusing on data engineering and technical architecture.
Responsibilities and impact
The candidate will design, develop, and maintain software components, participate in code and design reviews, automate testing, resolve technical issues, and contribute to disaster recovery and system monitoring activities.
Compensation and benefits
The pay range is $73,200 to $131,700, with pay based on factors like experience and education. Benefits include comprehensive health coverage, 401(k), employee discounts, paid leave, and relocation assistance for Minneapolis area.
Experience and skills
Requires a 4-year degree or equivalent, 1+ years in software development preferably in data engineering, experience with programming languages like Scala, Java, Python, and Spark, knowledge of cloud platforms, data migration tools, CI/CD, and SQL query languages.
Career development
Opportunities to learn new technologies, participate in research and proof-of-concept initiatives, and build domain-specific expertise through formal training and self-education.
Work environment and culture
Target emphasizes values and culture focused on helping families, with a hybrid work model requiring presence in Minneapolis or nearby, supporting work-life balance and inclusivity.
Company information
Target is a retail company focused on enhancing everyday life for families, offering competitive benefits and a supportive work environment.
Job location and travel
The role is hybrid based in Minneapolis, MN, requiring residency in or near Minneapolis with relocation assistance available.
Application process
Applicants must apply before 07/19/2025 and can request accommodations for disabilities via Target's HR email; detailed benefits information is provided via a URL.
Unique job features
The role offers a hybrid work arrangement, involvement in cutting-edge data engineering projects, and a focus on balancing software quality with delivery speed.
Company overview
Target Corporation is a leading American retail company known for offering a wide range of products including apparel, electronics, groceries, and home goods. They generate revenue through both in-store sales and a robust e-commerce platform. Founded in 1902 as Goodfellow Dry Goods, Target has a rich history of innovation, including the introduction of the first discount store in 1962. The company is also recognized for its commitment to corporate social responsibility, including sustainability initiatives and community engagement programs.
How to land this job
Tailor your resume to highlight your experience with data engineering tools such as Hadoop, Hive, Spark, and programming languages like Scala, Java, and Python, emphasizing your ability to build scalable, secure, and high-performance data solutions.
Focus on showcasing your knowledge of cloud platforms (Google Cloud, AWS, Azure), CI/CD processes, and your understanding of distributed programming and software design patterns, as these are key to the role.
Apply through multiple channels including Target's corporate careers site and LinkedIn to maximize your chances and visibility for the Data Engineer position.
Connect with current Target employees in the data engineering or technology divisions on LinkedIn, using ice breakers like commenting on recent Target technology initiatives or asking about their experience working on scalable data platforms.
Optimize your resume for ATS by incorporating keywords from the job description such as 'data engineering,' 'Hadoop,' 'Spark,' 'cloud platforms,' 'CI/CD,' and 'distributed programming' to ensure your resume passes initial automated screenings.
Utilize Jennie Johnson's Power Apply feature to automate the application process across multiple platforms, tailor your resume for ATS, and identify LinkedIn connections to network with, allowing you to focus your energy on interview preparation and skill development.
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