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About Us:

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.

About the Role:

As a Lead Data Engineer at Target, you serve as the technical anchor for the data engineering team that supports our products. You create, own, and are responsible for the data architecture that best serves our product needs, both functionally and non-functionally. You identify and drive architectural changes to accelerate feature development or improve the quality of service (or both). You have deep and broad engineering skills and are capable of designing and implementing a complete data architecture on your own, but you choose to influence a wider team by acting as a “force multiplier.” Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.

Responsibilities:

• Technical Leadership : Use your technology acumen to apply and maintain knowledge of current and emerging data technologies within specialized areas of the technology domain. Evaluate new technologies and participate in decision-making, accounting for several factors such as viability within Target’s technical environment, maintainability, and cost of ownership.

• Research & Development : Initiate and execute research and proof-of-concept activities for new data technologies.

• Strategic Planning : Lead or set strategy for testing and debugging at the platform or enterprise level. Serve as an expert resource in creating and improving standards and best practices to ensure high-performance, scalable, repeatable, and secure data solutions.

• Design & Lifecycle Management : Lead the design, lifecycle management, and total cost of ownership of data services. Provide the team with thought leadership to promote re-use and develop consistent, scalable patterns.

• Enterprise Impact : Participate in planning data services that have enterprise impact. Provide suggestions for handling routine and moderately complex technical problems, escalating issues when appropriate.

• Data Analysis : Gather information, data, and input from a wide variety of sources; identify additional resources when appropriate, engage with stakeholders, and conduct in-depth analysis of information.

• Project Management : Develop plans and schedules, estimate resource requirements, and define milestones and deliverables. Monitor workflow and risks; play a leadership role in mitigating risks and removing obstacles.

• Implementation & Automation : Lead and participate in complex data construction, automation, and implementation activities, ensuring successful implementation with architectural and operational requirements met.

• Standards & Best Practices : Establish new standards and best practices to monitor, test, automate, and maintain data systems. Serve as an expert resource in disaster recovery and disaster recovery planning.

• Continuous Learning : Stay current with Target’s technical capabilities, infrastructure, and technical environment. Maintain deep technical knowledge within areas of expertise.

• Data Modeling: Develop fully attributed data models, including logical, physical, and canonical. Influence data standards, policies, and procedures.

• Optimization : Install, configure, and/or tune data management solutions with minimal guidance. Monitor data management solutions and identify optimization opportunities.

About You:

• Education : 4-year degree or equivalent experience

• Experience : 7+ years of software development experience with at least one full cycle implementation

• Domain Knowledge : Demonstrates strong domain-specific knowledge regarding Target’s technology capabilities and key competitors’ products and differentiating features

• Technical Expertise : Demonstrates broad and deep expertise in multiple computer languages and frameworks (e.g., open source). Designs, develops, and approves end-to-end functionality of a product line, platform, or infrastructure. Is proficient in building Data Pipelines using Scala, Spark, Hadoop, HiveQL etc, and streaming frameworks such as Kafka. Good to have experience in building near real time data systems.

• Communication Skills : Communicates and coordinates with project team, partners, and stakeholders

• System Analysis & Optimization : Demonstrates expertise in analysis and optimization of systems capacity, performance, and operational health

• Data Lifecycle Management : Understands and develops solutions to foster data lifecycle management

• Technical Knowledge : Maintains deep technical knowledge within areas of expertise. Stays current with new and evolving technologies via formal training and self-directed education

• Scalability : Experience in building highly scalable distributed systems

Join Us:

If you are passionate about leading data engineering initiatives and driving innovation in data strategies, apply now and become a part of a dynamic team that values groundbreaking thinking and visionary goals.