Lead Data Engineer - Finance Tech

• 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
• 7 plus 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

This position will operate as a Hybrid/Flex for Your Day work arrangement based on Target’s needs. A Hybrid/Flex for Your Day work arrangement means the team member’s core role will need to be performed both onsite at the Target HQ MN location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target. Click here if you are curious to learn more about Minnesota.