Senior Engineer - Backend data

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Job Id: R0000451881

About Target
Target is an iconic brand, a Fortune 50 company, and one of America’s leading retailers.
Target as a tech company? Absolutely. We are the behind-the-scenes powerhouse that fuels Target’s passion and commitment to cutting-edge innovation. Our teams build and operate the technology that powers every part of Target’s digital and store experience. We combine modern engineering practices, cloud technologies, data, and innovative thinking to deliver reliable, scalable solutions that create meaningful value for our guests and team members.
Our high-performing teams balance independence with collaboration, and we pride ourselves on being versatile, agile, and creative. We are committed to building technology that operates smoothly, securely, and reliably while continuously exploring new ways to solve complex business problems.

About the Role
As a Senior Data Engineer, you will play a key role in designing, developing, and optimizing large-scale data platforms and pipelines that support critical business and analytical use cases. You will work across the full data lifecycle, from data ingestion and transformation to storage, processing, quality, and consumption.
You will apply strong expertise in Big Data, Apache Spark, Scala, and Google BigQuery to build high-performance, scalable, and reliable data solutions. You will work closely with engineers, architects, product teams, data scientists, and business partners to translate complex requirements into robust technical solutions.
The ideal candidate combines strong data engineering fundamentals with a passion for solving complex problems, optimizing large-scale workloads, and continuously learning emerging technologies. Experience with Java/Spring Boot and exposure to AI-assisted engineering tools such as GitHub Copilot and Claude will be an added advantage.
What You’ll Do

  • Design, develop, and maintain scalable data pipelines and data processing frameworks using Spark, Scala, BigQuery, and other Big Data technologies.
  • Build robust ETL/ELT pipelines for high-volume and complex datasets.
  • Develop efficient data models and optimize BigQuery tables using appropriate partitioning, clustering, query design, and storage strategies.
  • Design and implement scalable batch and distributed data processing solutions using Apache Spark.
  • Develop reusable frameworks and components to improve engineering productivity, data processing efficiency, and operational reliability.
  • Analyze and optimize large-scale data workloads for performance, scalability, reliability, and cloud cost efficiency.
  • Implement data quality, validation, monitoring, and observability across data pipelines and datasets.
  • Troubleshoot complex data, pipeline, infrastructure, and production issues and drive root-cause resolution.
  • Participate in architecture and design discussions and contribute to technical decisions involving data platforms and cloud technologies.
  • Collaborate with Product, Analytics, Data Science, Architecture, and other engineering teams to deliver high-quality data products.
  • Participate in code reviews, design reviews, testing, debugging, and production support activities.
  • Follow engineering best practices around CI/CD, automation, security, reliability, and operational excellence.
  • Evaluate and adopt emerging technologies that improve data engineering productivity and platform capabilities.
  • Contribute to technical documentation, engineering standards, and knowledge-sharing across the team.
  • Explore and adopt AI-assisted development tools such as GitHub Copilot, Claude, and similar solutions to improve developer productivity and engineering efficiency.
  • Identify practical opportunities to leverage Generative AI for code development, code reviews, debugging, documentation, data analysis, and automation.
  • Stay current with emerging AI and data engineering technologies and evaluate their applicability to Target's technology ecosystem.
About You
  • Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent practical experience.
  • 5+ years of experience in software or data engineering, with significant experience building and supporting large-scale data platforms.
  • Strong hands-on experience with:
    • Apache Spark
    • Scala
    • Google BigQuery
    • Big Data / Distributed Processing
    • Data Warehousing
    • ETL/ELT
  • Strong SQL skills and experience working with large and complex datasets.
  • Experience designing and optimizing data pipelines for high-volume, high-performance processing.
  • Strong understanding of distributed computing concepts, data partitioning, joins, aggregation, scalability, and performance optimization.
  • Experience with cloud-based data platforms, preferably Google Cloud Platform (GCP).
  • Good understanding of data modeling, including fact/dimension models and analytical data structures.
  • Experience with data quality, monitoring, observability, and production support.
  • Strong problem-solving skills with the ability to independently troubleshoot complex technical issues.
  • Ability to participate in architecture discussions and translate business requirements into scalable technical solutions.
  • Strong communication and collaboration skills.
Preferred / Good-to-Have Skills
  • Java and Spring Boot experience.
  • Experience building REST APIs or microservices.
  • Kafka or other event-streaming technologies.
  • Experience with cloud-native architectures and GCP services.
  • Experience with Python and Shell scripting.
  • Experience with CI/CD tools such as Jenkins, GitHub Actions, or similar platforms.
  • Experience with containerization technologies such as Docker.
  • Experience with data quality platforms such as Monte Carlo or equivalent.
  • Exposure to Generative AI and AI-assisted development tools, including GitHub Copilot, Claude, or similar tools.
  • Experience developing or contributing to reusable data engineering frameworks.
  • Experience in Retail, AdTech, Media, Analytics, or other high-volume data domains is a plus.

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Competitive benefits

We are proud to provide benefits that support you, your family and your future.

Health and well-being

Target in India (TII) prioritizes our people by offering healthcare support, fitness programs, teleheath benefits (i.e., screenings and consultations) and 24/7 confidential mental well-being telecounseling support.

Financial well-being

Your financial well-being is bright with TII's comprehensive flexible insurance program, National Pension System, learning assistance program, day care support and much more.

Paid time off

TII encourages work-life balance with paid time off like privilege, casual, bereavement and parental leaves that offer support in all stages of life.

Competitive pay

TII knows our people are everything and proudly provides equitable and competitive pay.

Other benefits

From digitalized cafeteria solutions to transportation services to broadband reimbursement, enjoy special everyday perks.

Creating a culture of joy

We bring out the best in each other every day.

A group of Target team members giving each other a thumbs up as they huddle in the back of the store.

Inclusivity

We value diverse voices and approaches. We act with authenticity and respect. We create equitable experiences for all.

Connection

We build trusted relationships. We collaborate across business functions. We recognize and celebrate progress.

Drive

We do what is right for Target, our team and guests. We deliver results that matter. We continually learn by valuing progress over perfection.

Grow with Target

We are fully invested in your personal and professional growth because our people are our power. 

Target's leadership truly empowers personal and professional growth, fostering an environment where we care, grow and win together.

Sandeep Sr. Engineering Manager – Target Tech, Corporate

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