Lead Data Engineer 4

As a Data Engineer IV at Flipkart, you will play a critical role in shaping the company's data ecosystem at scale. You will partner closely with business and analytics teams to design and build robust, scalable, and high-performance data platforms and pipelines that power decision-making across the organization.
The core responsibilities for the job include the following:
Business and Domain Understanding:
Collaborate closely with Analysts, Product Managers, and Business stakeholders to understand complex business problems across Flipkart's ecosystem.
Translate business requirements into scalable and efficient data solutions.
Drive data architecture decisions aligned with business goals.
Data Pipelines and Data Models (CDM):
Design and build highly scalable, reliable, and efficient data pipelines.
Develop and maintain Common Data Models (CDMs) that standardize data across domains.
Ensure pipelines are optimized for large-scale data processing and diverse business use cases.
System Design and Trade-offs:
Architect data solutions by balancing: Performance, Scalability, Cost efficiency, Data modeling principles, Flexibility for evolving business needs.
Lead design reviews and influence best practices in data engineering.
Big Data Technology Expertise:
Work extensively with modern big data technologies, including Apache Spark, Apache Flink, Apache Kafka, Google BigQuery, Dataproc, and Apache Iceberg.
Programming languages: Scala and Python.
Evaluate and adopt new technologies to improve platform capabilities.
Data Quality and Reliability:
Build systemic frameworks to monitor, measure, and improve data quality.
Implement automated checks, anomaly detection, and data validation systems.
Drive root cause analysis and resolution of data issues across pipelines.
Requirements:
Bachelor's/Master's degree in Computer Science, Engineering, or a related field.
8-12+ years of experience in data engineering or related fields.
Strong experience in building large-scale distributed data systems.
Preferred Qualifications:
Deep expertise in distributed computing frameworks like Spark/Flink.
Strong understanding of data modeling techniques (OLAP, dimensional modeling, etc. ).
Experience with real-time and batch data processing architectures.
Proven ability to design systems handling high data volume and velocity.
Strong problem-solving skills and ability to work in ambiguous environments.
What We're Looking For:
Strong ownership and leadership mindset.
Ability to influence architecture and technical decisions.
Excellent collaboration and communication skills.
Passion for solving complex data problems at scale.

Experience
8-12 yrs