Data Engineer – Python & AWS

Important Note (Please Read Before Applying)

🚫 Do NOT apply if:

You have less than 5 years or more than 8 years of total experience

You do not have hands-on experience with key AWS data services (Glue, Lambda, EMR, Redshift, S3)

You have limited or no Python programming background

You are on a notice period longer than 30 days

You are looking for remote-only work (role may require hybrid/on-site collaboration)

You have no real-time experience in designing or maintaining ETL/ELT data pipelines

✅ Apply ONLY if you meet ALL mandatory skills and criteria above.

Job Title:

Location:

Years of Experience:

About the Company

Our client is a trusted global innovator of IT and business services, present in 50+ countries. They specialize in digital & IT modernization, consulting, managed services, and industry-specific solutions. With a commitment to long-term success, they empower clients and society to move confidently into the digital future.

We are seeking a highly skilled Data Engineer with strong expertise in AWS cloud services and Python programming. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines, ensuring data availability, quality, and performance across enterprise systems. You will collaborate closely with data analysts, data scientists, and business stakeholders to deliver reliable, high-quality data solutions.

Total experience : 5 to 8 years

Key Responsibilities

● Design, develop, and maintain ETL/ELT data pipelines using Python and AWS native services (Glue, Lambda, EMR, Step Functions, etc.)

● Build and manage data lakes and data warehouses using Amazon S3, Redshift, Athena, and Lake Formation

● Implement data ingestion from diverse sources (RDBMS, APIs, streaming data, on-premise systems)

● Optimize data workflows for performance, cost, and reliability using AWS tools like Glue Jobs, Athena, and Redshift Spectrum

● Develop reusable, modular Python-based frameworks for data ingestion, transformation, and validation

● Work with stakeholders to understand data requirements, model data structures, and ensure data consistency and governance

● Deploy and manage data infrastructure using Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation

● Implement data quality, monitoring, and alerting using CloudWatch, Glue Data Catalog, or third-party tools

● Support data security and compliance (IAM roles, encryption, data masking, GDPR policies, etc.)

● Collaborate with DevOps and ML teams to integrate data pipelines into analytics and AI workflows

Required Skills & Qualifications

● Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.

● 5 to 8 years of experience as a Data Engineer or similar role.

● Strong programming experience in Python (pandas, boto3, PySpark, SQLAlchemy, etc.)

● Deep hands-on experience with AWS services, including:

○ AWS Glue, Lambda, EMR, Redshift, Athena, S3, Step Functions

○ IAM, CloudWatch, Kinesis (for streaming), and ECS/EKS (for containerized workloads)

● Experience with SQL and NoSQL databases (e.g., PostgreSQL, DynamoDB, MongoDB)

● Strong knowledge of data modeling, schema design, and ETL orchestration.

● Familiarity with version control (Git) and CI/CD pipelines for data projects.

● Understanding of data governance, lineage, and cataloging principles.

● Excellent problem-solving, debugging, and performance-tuning skills.

Preferred / Nice-to-Have Skills

● Experience with Apache Spark or PySpark on AWS EMR.

● Exposure to Airflow, dbt, or similar workflow orchestration tools.

● Knowledge of containerization (Docker, Kubernetes) and DevOps practices.

● Experience with machine learning data pipelines or real-time streaming (Kafka, Kinesis).

● Familiarity with AWS Glue Studio, AWS DataBrew, or AWS Lake Formation.

✅ Mandatory Skills

✔ Strong expertise in AWS Cloud Services – Glue, Lambda, EMR, Step Functions, S3, Redshift, Athena

✔ Hands-on experience in Python programming (pandas, boto3, PySpark, SQLAlchemy, etc.)

✔ Proven experience in building and maintaining ETL/ELT data pipelines on AWS

✔ Experience with data lake and data warehouse design (S3, Redshift, Lake Formation)

✔ Strong SQL and data modeling skills (RDBMS, NoSQL – DynamoDB/MongoDB)

✔ Hands-on experience with IaC tools like Terraform or AWS CloudFormation

✔ Experience in data quality, monitoring, and governance (Glue Data Catalog, CloudWatch, IAM)

✔ Familiarity with Git, CI/CD pipelines, and Agile methodologies