Senior Data Engineering Team Lead - Customer Service Analytics Platform

Senior Data Engineering Team Lead - Customer Service Analytics Platform

IMMEDIATE START REQUIRED

Project Overview

Lead a 3-month initiative to build and deploy a production-ready data pipeline on AWS for real-time sentiment analysis and productivity measurement of customer service agents. This role combines hands-on technical leadership with strategic project management in a fast-paced, deadline-driven environment.

⚡ URGENT: Project kickoff scheduled within 2 weeks - seeking immediate availability

Key Responsibilities

Technical Leadership (60%)

• Design and implement scalable AWS data pipeline architecture (Kinesis, Lambda, Step Functions, S3)

• Lead integration of LLM-based sentiment analysis with cost optimization strategies

• Architect real-time analytics solutions using Kinesis Analytics or MSK/Kafka Streams

• Implement monitoring, observability, and alerting across the entire data pipeline

• Ensure production-ready code quality, testing, and deployment practices

Team Management (25%)

• Lead cross-functional team of 3-5 engineers (data engineers, backend developers)

• Conduct daily standups, sprint planning, and technical architecture reviews

• Mentor junior team members on AWS best practices and data engineering patterns

• Collaborate with business stakeholders to translate requirements into technical solutions

Project Delivery (15%)

• Own end-to-end project timeline and milestone delivery within 3-month deadline

• Manage technical risks, dependencies, and escalation paths

• Present technical progress and business metrics to executive stakeholders

• Ensure seamless handover to production support team

Required Experience

Technical Foundation

• 5+ years data engineering experience with 3+ years on AWS platform

• Expert-level knowledge of AWS data services (Kinesis, Lambda, Glue, S3, DynamoDB)

• Production experience with event-driven architectures and stream processing

• Strong background in API integration and cost optimization for cloud services

• Experience with LLM integration (OpenAI, Anthropic, AWS Bedrock) and prompt engineering

Leadership & Project Management

• 2+ years leading technical teams of 3-5 engineers

• Proven track record delivering data projects under tight deadlines (3-6 months)

• Experience with agile methodologies and technical project management

• Strong communication skills for both technical and business audiences

Domain Knowledge (Preferred not required)

• Previous work with customer service analytics, call center metrics, or contact center data

• Understanding of productivity metrics (AHT, CSAT, FCR) and operational KPIs

• Experience with real-time dashboard development and business intelligence

Technical Skills

• Languages: Python / JavaScript / Node.js, SQL, bash scripting

• AWS Services: Kinesis, Lambda, Step Functions, S3, DynamoDB, RDS, CloudWatch

• Streaming: Kafka, Kinesis Analytics, real-time data processing

• ML/AI: LLM API integration, sentiment analysis, prompt optimization

• DevOps: CI/CD pipelines, Infrastructure as Code (CloudFormation/CDK)

• Monitoring: CloudWatch, X-Ray, distributed tracing

• Frontend Integration: Experience with dashboard frameworks and real-time data visualization

Availability Requirements

• Start Date: Immediate (within 1-2 weeks maximum)

• Commitment: Full-time availability for 3-month project duration

• Notice Period: Maximum 2 weeks accepted

• Flexibility: Ability to work extended hours during critical project phases

Flexible Work Arrangement

• No non-compete clauses: We believe in talent freedom and don't restrict your future opportunities

• Overemployment accepted: We understand modern work realities - if you have other commitments that don't interfere with project delivery and short notice availability, we're open to discussion

• Focus on results: As long as you can deliver on tight deadlines and be available for urgent project needs, we care about output, not exclusivity

Project Support & Onboarding

• Dedicated knowledge transfer: You'll have direct access to a team member who previously worked on this client's projects

• Domain expertise support: Get up to speed quickly with existing client context, technical decisions, and business requirements

• Mentorship available: Previous team lead will provide guidance on client preferences, architectural patterns, and project-specific best practices

What We Offer

• Opportunity to lead cutting-edge AI/ML data infrastructure project

• Direct impact on customer service operations and agent productivity

• Collaborative environment with executive visibility

• Competitive compensation package + project completion bonus

• Growth-focused small company: Join a rapidly expanding startup where you can grow alongside the business

• Post-project opportunities: Strong potential for continued collaboration and expanded roles after successful 3-month delivery

• No glass ceiling: In our fast-growing environment, your career trajectory is limited only by your ambition and performance

• Ownership mentality: Shape the technical direction and build the foundation for our data platform's future

Project Timeline:

• Week 1-2: Architecture design and team setup

• Week 3-8: Core development and integration

• Week 9-12: Testing, optimization, and production deployment

Beyond the Project: This 3-month engagement is designed as a proving ground for exceptional talent. Successful project leads will have first priority for:

• Head of Data Engineering positions as we scale

• Technical co-founder opportunities in new ventures

• Equity participation in company growth

• Leadership roles across multiple product lines

Team Size: 3-5 engineers Reporting: [CEO]

This is a high-impact, fast-paced role perfect for a senior engineer ready to take on technical leadership while building their long-term career in a dynamic, growth-oriented environment. We value talent flexibility and results over traditional employment constraints.

To Apply: Please include your earliest available start date and any current commitments that might affect immediate availability.