Aws Data Engineer

Key Responsibilities:

• Design, develop, and maintain robust ETL/ELT pipelines to collect, clean, transform, and load data from diverse sources.
• Build and optimize data warehouses and data lakes using modern cloud platforms (e.g., GCP, AWS, Azure).
• Work with structured and unstructured data from various systems (databases, APIs, flat files, etc.).
• Collaborate with data scientists and analysts to prepare data for analytical models and dashboards.
• Monitor and improve pipeline performance, scalability, and reliability.
• Ensure data quality, data governance, and compliance across the data ecosystem.
• Automate data workflows, implement data versioning, and handle orchestration using tools like Apache Airflow, Cloud Composer, or equivalent.
• Document data sources, models, and pipelines for maintainability and transparency.

Mandatory Skills:

• Proficiency in SQL and performance tuning for large-scale datasets.
• Strong programming skills in Python or Scala for data processing.
• Solid understanding of ETL/ELT processes and data modeling concepts.
• Experience with cloud data platforms such as:
• GCP (BigQuery, Cloud Storage, Dataflow)
• or AWS (Redshift, S3, Glue)
• or Azure (Data Factory, Synapse)
• Familiarity with tools like Apache Spark, Kafka, Informatica, or dbt.