Lead Data Engineer

avature

Bengalor 7 Years Exp Posted 18d ago

Job Description

Data Engineering & Platform Development

· Design, develop, and maintain scalable data pipelines using AWS serverless technologies including Amazon S3, AWS Lambda, AWS Glue, Redshift Serverless, Step Functions, and EventBridge.

· Build robust ETL/ELT frameworks to ingest, transform, validate, and publish data from multiple enterprise sources.

· Develop reusable data ingestion and transformation components to accelerate onboarding of new datasets.

· Implement CDC (Change Data Capture), incremental processing, and event-driven architectures.

· Optimise Redshift workloads, SQL processing, storage strategies, and query performance.

· Establish data quality, monitoring, reconciliation, and alerting frameworks.

Full Stack Application Development

· Design and develop self-service applications and internal data products.

· Build RESTful APIs and backend services using Python and AWS Lambda.

· Develop responsive web applications using modern front-end frameworks such as React, Angular, or Vue.

· Integrate applications with AWS services, authentication mechanisms, and enterprise platforms.

· Create intuitive user experiences enabling business users to access, analyse, and manage data without technical expertise.

Architecture & Technical Leadership

· Define end-to-end solution architecture for data and analytics platforms.

· Lead technical design reviews, code reviews, and architecture governance activities.

· Drive adoption of cloud-native and serverless design patterns.

· Establish engineering standards, CI/CD automation, security controls, and operational best practices.

· Mentor and coach engineers on software engineering, data engineering, and cloud architecture.

Operations & Reliability

· Ensure platform availability, scalability, performance, and resiliency.

· Implement proactive monitoring using CloudWatch, logging, dashboards, and automated alerting.

· Perform root cause analysis and resolve production issues.

· Define and manage SLA, data freshness, and reliability metrics.

· Continuously improve platform performance, security, and cost efficiency.

Stakeholder Engagement

· Collaborate with business stakeholders, product owners, architects, and engineering teams.

· Translate business problems into scalable technical solutions.

· Communicate technical concepts effectively to both technical and non-technical audiences.

· Drive innovation by identifying opportunities for automation, self-service, and AI-driven capabilities.

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