Lead Data Engineer - Finance Technology (Hadoop, PySpark, Scala/Java)

As a Lead Data Engineer, you will serve as the technical lead for the engineering team, designing and developing scalable, high-performance data solutions. You will drive the evolution of our data architecture, ensuring it meets both functional and non-functional business requirements while delivering reliability, efficiency, and scalability. Your expertise in big data technologies, distributed systems, and cloud platforms will help shape the engineering roadmap and establish best practices for data processing, analytics, and real-time data services. You will play a key role in architecting and optimizing data pipelines using Hadoop, Spark, Scala/Java, and cloud technologies to support enterprise-wide data initiatives., * Architect and build scalable, high-performance data pipelines and distributed data processing solutions using Spark, Scala/Java and cloud platforms (AWS, GCP, or Azure)

• Design and implement real-time and batch data processing solutions, ensuring data is efficiently processed and readily available for analytical and operational use
• Develop APIs and data services that provide low-latency, high-throughput access to data for downstream applications, enabling real-time decision-making
• Optimize and enhance data models, workflows, and processing frameworks to improve performance, scalability, and cost efficiency
• Drive data governance, security, and compliance best practices
• Collaborate with product teams and business stakeholders to understand requirements and deliver data-driven solutions
• Lead the design, implementation, and lifecycle management of data services and platforms
• Stay current with emerging technologies and promote the adoption of best practices in big data engineering, cloud computing, and API development
• Provide technical leadership and mentor engineers to foster engineering excellence and best practices

Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.

• BS or MS in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics or a related technical field preferred
• 7plus years of experience in data engineering, software development, or distributed systems
• Expertise in Big Data technologies such as Hadoop, Spark, and distributed processing frameworks
• Strong programming skills in PySpark, Scala, and/or Java
• Experience with cloud platforms (AWS, GCP, or Azure) and associated data services (e.g. S3, BigQuery, Databricks, EMR, Snowflake)
• Proficiency in API development using REST, GraphQL, or gRPC to support real-time and batch data access
• Experience with real-time and streaming data architectures like Kafka, Flink or Kinesis
• Strong knowledge of data modeling, ETL pipeline design and performance optimization
• Understanding of data governance, security, and compliance in large-scale data environments
• Strong problem-solving skills and the ability to thrive in complex, evolving environments
• Excellent communication and collaboration skills, with experience working across cross-functional teams

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here (https://corporate.target.com/about) . About the Team: Finance Technology within Core Retail Services powers the financial backbone of Target's enterprise operations. We build and support platforms that enable critical business capabilities across Accounts Payable, Accounts Receivable, Vendor Income, Treasury, Financial Planning, Core Accounting, Revenue & Receivables, and Enterprise Financial Controls. Our financial reporting platform brings these data domains together to deliver near real-time insights, enabling accurate financial reporting and faster, data-driven decision-making. Join our global in-house technology team of more than 5,000 engineers, data scientists, architects, and product managers who are striving to make Target the most convenient, safe, and joyful place to shop. We use agile practices and leverage open-source technologies to build best-in-class solutions for our team members and guests.