Job Overview:
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.
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 FormationImplement 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 SpectrumDevelop reusable, modular Python-based frameworks for data ingestion, transformation, and validationWork with stakeholders to understand data requirements, model data structures, and ensure data consistency and governanceDeploy and manage data infrastructure using Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormationImplement data quality, monitoring, and alerting using CloudWatch, Glue Data Catalog, or third-party toolsSupport 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.Minimum 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 FunctionsIAM, 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 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.,
Soft Skills
Strong analytical and communication skills.Ability to work independently and in cross-functional teams.Passion for automation and continuous improvement.Adaptability in fast-paced, evolving cloud environments.
27 days ago
25 days ago
