Lead AWS Data Engineer/ Lead Data Engineer/AWS Data Architect

IBOTIX US Inc.
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Tech stack

Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Business Intelligence
Big Data
Code Review
Computer Programming
Continuous Delivery
Data Architecture
Information Engineering
Data Integration
ETL
Data Security
Data Systems
Data Warehousing
Software Debugging
Distributed Computing Environment
Github
Identity and Access Management
Python
Query Optimization
Unstructured Data
Workflow Management Systems
Data Processing
Cloud Platform System
Real Time Systems
Data Ingestion
Delivery Pipeline
Spark
State Machines
Electronic Medical Records
GIT
Cloudformation
Data Lake
PySpark
Infrastructure Automation Frameworks
Amazon Web Services (AWS)
Kafka
Video Streaming
Functional Programming
Cloudwatch
REST
Terraform
Data Pipelines
Jenkins
Redshift

Job description

We are seeking an experienced Lead AWS Data Engineer/ Lead Data Engineer/AWS Data Architect with 8+ years of experience designing, building, and optimizing scalable cloud-based data platforms. The ideal candidate will possess deep expertise in AWS data services, distributed data processing, ETL/ELT development, and data warehousing. This role requires strong technical leadership, hands-on development, and the ability to mentor engineers while collaborating with architects, business stakeholders, and cross-functional teams to deliver enterprise-grade data solutions., * Design, develop, and maintain scalable data pipelines using AWS cloud-native services.

  • Build high-performance ETL/ELT workflows for structured, semi-structured, and unstructured data.
  • Develop data ingestion frameworks for batch and real-time processing.
  • Architect and optimize enterprise data lakes and data warehouse solutions.
  • Implement data modeling techniques for analytical and reporting requirements.
  • Lead technical design discussions and provide architectural guidance.
  • Optimize data processing performance, scalability, and cost efficiency.
  • Develop reusable frameworks, utilities, and automation for data engineering.
  • Ensure data quality, governance, lineage, and security best practices.
  • Collaborate with Data Scientists, BI Developers, Product Owners, and business stakeholders.
  • Perform code reviews and mentor junior data engineers.
  • Support CI/CD pipelines and infrastructure automation.
  • Troubleshoot production issues and perform root cause analysis.
  • Document technical solutions, architecture, and operational procedures.

Requirements

  • 8+ years of hands-on experience in Data Engineering.
  • Strong expertise with AWS Cloud.
  • Experience with AWS Glue, Amazon Redshift, Amazon S3, Lambda, EMR, Athena, Kinesis, RDS, Step Functions, CloudWatch, and IAM.
  • Strong programming skills in Python and PySpark.
  • Experience with Apache Spark for large-scale data processing.
  • Advanced SQL development and query optimization.
  • Experience building ETL/ELT pipelines.
  • Hands-on experience with data lakes and modern data architectures.
  • Experience with workflow orchestration tools such as Apache Airflow or AWS Managed Workflows for Apache Airflow (MWAA).
  • Knowledge of streaming technologies such as Kafka or Amazon Kinesis.
  • Experience implementing CI/CD using Git, Jenkins, GitHub Actions, or AWS CodePipeline.
  • Familiarity with Infrastructure as Code using Terraform or AWS CloudFormation.
  • Experience with REST APIs and data integration.
  • Strong understanding of data security, encryption, and AWS best practices.
  • Excellent debugging, analytical, and problem-solving skills.

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