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Job Description
Structured overview of role & requirementsAbout This Role
Develop and optimize a high-performance, scalable Data Lake-house architecture aimed at achieving sub-minute data latency.
Manage complex Change Data Capture (CDC) workflows, optimize distributed query engines, and integrate AI tools to enhance development efficiency.
Lead technical initiatives including preparing Technical Requirement Documents (TRD), conducting design reviews, and interacting with product and key stakeholders to align data analytics with business workflows.
Minimum Requirements
3–5 years of experience in Data Engineering with expertise in distributed systems and cloud-native architectures.
Expert-level proficiency in Python/PySpark and SQL; familiarity with Go, Java, or Scala is a plus.
Hands-on experience with AWS services including S3, EKS, MSK, and Infrastructure-as-Code tools.
Experience with workflow orchestration tools such as Airflow or Temporal.
Ideal Candidate Profile
Strong systems thinking to evaluate trade-offs between storage formats and processing frameworks in a Lakehouse environment.
Proven ability to lead technical teams and initiatives, including designing domain models for OLAP (Fact, Dimension, SCDs, OBT pattern tables).
Experienced in leveraging AI-assisted coding tools (Claude, Codex, Copilot) to accelerate development lifecycle.