AWS Data Engineer

JOB TITLE

• Lead Data Engineer – Python & AWS

EXPERIENCE

• 8–10 years total

  (minimum 7

  + years

  relevant data engineering experience)

ROLE OVERVIEW:

• Design, build, and optimize

  scalable data platforms on AWS

• Own

  end-to-end data pipelines

  , data lakes, and data warehouses
• Lead technical execution while

  mentoring data engineers

• Enable

  analytics, reporting, and AI/ML workloads

KEY RESPONSIBILITIES:

• Design and build

  AWS-based data pipelines

• Develop

  Python ETL/ELT frameworks

• Build and manage

  data lakes & warehouses

• Integrate data from

  databases, APIs, streaming, and SaaS sources

• Optimize

  data models, schemas, and performance

• Ensure

  data quality, monitoring, and governance

• Implement

  CI/CD for data pipelines

• Review code and

  mentor junior engineers

• Collaborate with

  Analytics, Data Science, Product, DevOps

REQUIRED SKILLS:

• Python

  (pandas, PySpark, boto3)

• AWS Data Services

• Glue, EMR, Lambda, Step Functions
• S3, Redshift, Athena
• Kinesis

• SQL & Data Modeling

• ETL / ELT pipelines

• CI/CD & Git

• AWS Security

  (IAM, encryption)

• Performance tuning & troubleshooting

GOOD-TO-HAVE

• Spark / PySpark
• Airflow, dbt, Dagster
• Kafka or real-time streaming
• Docker / Kubernetes
• SageMaker or QuickSight
• AWS Certifications

SOFT SKILLS

• Strong ownership and accountability
• Mentoring and leadership mindset
• Clear communication with stakeholders
• Agile team experience

IDEAL CANDIDATE

• Hands-on AWS data engineer
• Strong Python + SQL background
• Experience leading production data platforms
• Comfortable owning systems end-to-end