Lead Data Engineer (1 Position)

About the Role

Were building a next-generation Data Analytics Engine that transforms raw market and historical data into actionable intelligence for the electronics supply chain industry. Our platform ingests, processes, and analyzes high-volume data across suppliers, parts, and trends powering real-time insights and ML-driven applications.

highly experienced Lead or Staff Data Engineer

Key Responsibilities

• Design, implement, and optimize

  scalable ETL pipelines

  for billions of records using

  AWS-native tools

  (Glue, Step Functions, S3, PostgreSQL).
• Migrate and evolve existing pipelines toward

  open-source orchestration tools

  such as

  Apache Airflow and Kafka

  .
• Lead

  data lake and data warehouse architecture design

  for analytics and ML workflows.
• Own and maintain

  CI/CD workflows

  ensuring reliability, observability, and deployment automation.
• Implement

  data validation, schema evolution, anomaly detection, and data quality checks

  .
• Contribute to

  Infrastructure as Code (Terraform, AWS CDK)

  for reproducible deployments.
• Provide

  technical mentorship

  , make architectural decisions, and establish best practices.

Required Qualifications

• 8+ years

  of experience as a Data Engineer or similar role with production ownership.
• Expertise in

  AWS tools

  : Glue, Step Functions, S3, Athena, Lambda.
• Deep knowledge of

  open-source data stack

  : Apache Airflow, Spark, Kafka, dbt.
• Strong

  Python programming

  skills for modular workflows and automation.
• Expert-level

  SQL

  and experience with

  PostgreSQL

  (or similar databases).
• Experience with

  CI/CD tools

  (GitHub Actions, Jenkins, etc.).
• Familiarity with

  Infrastructure as Code

  : Terraform, AWS CDK, or CloudFormation.
• Ability to

  mentor engineers and lead architectural decisions

  .

Preferred Qualifications

• Background in

  ML/AI pipelines or feature engineering

  .
• Experience with

  serverless technologies

  or

  containerized deployments

  (Docker, Lambda).
• Familiarity with

  data observability tools and alerting systems

  .

Education

• Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or a related technical field

  (or equivalent practical experience).

What We Offer

• Opportunity to work on

  impactful, real-world problems

  in supply chain intelligence.

• Direct mentorship

  from experienced engineers and AI product leads.
• A

  flexible, startup-friendly environment

  where your contributions matter.
• Competitive compensation and opportunities for career growth.