Lead Engineer (Data Engineering)

About the Role: As a

Lead Data Engineer , you will serve as the

technical anchor for the engineering team, responsible for designing and developing

scalable, high-performance data solutions . You will

own and drive data architecture that supports both functional and non-functional business needs, ensuring

reliability, efficiency, and scalability . Your expertise in

big data technologies, distributed systems, and cloud platform s will help shape the engineering roadmap and best practices for

data processing, analytics, and real-time data servin g. You will play a key role in

architecting and optimizing data pipeline s using

Hadoop, Spark, Scala/Java, and cloud technologie s to support enterprise-wide data initiatives .Additionally,

experience with API development for serving low-latency dat a and

Customer Data Platforms (CDP ) will be a strong plus

Key Responsibilities:

• Architect and build scalable, high-performance data pipelines and distributed data processing solutions using Hadoop, Spark, Scala/Java, and cloud platforms (AWS/GCP/Azure).
• Design and implement real-time and batch data processing solutions, ensuring data is efficiently processed and made available for analytical and operational use.
• Develop APIs and data services to expose low-latency, high-throughput 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 data scientists, product teams, and business stakeholders to understand requirements and deliver data-driven solutions.
• Lead the design, implementation, and lifecycle management of data services and solutions.
• Stay up to date with emerging technologies and drive adoption of best practices in big data engineering, cloud computing, and API development.
• Provide technical leadership and mentorship to engineering teams, promoting best practices in data engineering and API design.

About You:

• 10+ years of experience, with 7+ years 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 Scala and/or Java (Python is a plus).
• Experience with cloud platforms (AWS, GCP, or Azure) and their data ecosystem (e.g., S3, BigQuery, Databricks, EMR, Snowflake, etc.).
• Proficiency in API development using REST, GraphQL, or gRPC to serve real-time and batch data.
• Experience with real-time and streaming data architectures (Kafka, Flink, Kinesis, etc.).
• Strong knowledge of data modeling, ETL pipeline design, and performance optimization.
• Understanding of data governance, security, and compliance in large-scale data environments.
• Experience with Customer Data Platforms (CDP) or customer-centric data processing is a strong plus.
• Strong problem-solving skills and ability to work in complex, unstructured environments.
• Excellent communication and collaboration skills, with experience working in cross-functional teams.

Why Join Us?

• Work with cutting-edge big data, API, and cloud technologies in a fast-paced, collaborative environment.
• Influence and shape the future of data architecture and real-time data services at Target.
• Solve high-impact business problems using scalable, low-latency data solutions.
• Be part of a culture that values innovation, learning, and growth.