AWS Data Engineer - Integration & Modelling

Description :

We are seeking an experienced AWS Data Engineer to design, build, and maintain scalable data pipelines and cloud-based data platforms on Amazon Web Services (AWS). The ideal candidate will have strong expertise in data integration, data modeling, ETL development, and cloud data architecture, with a focus on performance, scalability, and security.

Key Responsibilities :

- Design and implement data ingestion, transformation, and storage pipelines using AWS services such as Glue, Lambda, EMR, Redshift, and S3.

- Develop and optimize ETL/ELT workflows to support analytics, data science, and reporting requirements.

- Collaborate with data scientists, analysts, and business teams to understand data needs and ensure reliable data delivery.

- Build and maintain data lake and data warehouse architectures on AWS.

- Work with both structured and unstructured data, ensuring high quality, consistency, and availability.

- Manage data security, governance, and compliance according to organizational standards.

- Implement data validation, quality checks, and monitoring frameworks for pipelines.

- Optimize performance and cost across storage, compute, and data processing layers.

- Leverage Infrastructure as Code (IaC) tools like Terraform or CloudFormation for environment setup and automation.

- Support DevOps and CI/CD practices for automated data pipeline deployments.

Required Skills & Qualifications :

- Bachelors or Masters degree in Computer Science, Information Systems, Data Engineering, or a related field.

- 58 years of professional experience in data engineering, ETL development, or cloud data solutions.

Hands-on expertise in AWS data services such as :

- AWS Glue, S3, Lambda, Redshift, EMR, Athena, Step Functions, and Kinesis.

- Strong proficiency in SQL and Python for data processing and automation.

- Solid understanding of data modeling (OLTP and OLAP), data warehousing concepts, and performance tuning.

- Experience with ETL tools (AWS Glue, Talend, Informatica, dbt, or similar).

- Familiarity with big data technologies such as Spark, Hadoop, or PySpark.

- Knowledge of version control (Git) and CI/CD pipelines for data projects.

- Strong understanding of data security, encryption, and IAM policies in AWS.

Preferred Skills :

- Experience with streaming data solutions (Kafka, Kinesis Data Streams, or AWS MSK).

- Familiarity with modern data stack tools like dbt, Airflow, Snowflake, or Databricks.

- Exposure to MLOps or data science pipeline integration.

- Knowledge of API-based data integration and RESTful services.

- AWS certification such as :

- AWS Certified Data Analytics Specialty or AWS Certified Solutions Architect Associate/Professional.

Soft Skills :

- Strong problem-solving and analytical abilities.

- Excellent communication and collaboration skills.

- Ability to work independently and deliver in agile environments.

- Detail-oriented with a focus on data quality and reliability.