Data Engineer (SQL+Python+AWS)

We are looking for someone with the following skills : 1. Strong SQL and Data Modelling skills Hands-on experience writing complex SQL for data transformation, analytics, and performance optimization, with solid understanding of data modelling principles for warehouse/lake-house environments. 2. Python / modern programming for data engineering Proficiency in Python for building scalable ETL/ELT pipelines, data processing workflows, automation, and integration across data platforms. 3. Cloud data platform experience Practical experience with modern cloud ecosystems such as AWS, Azure, or GCP, including managed data services, storage, compute, and orchestration patterns. 4. Modern data pipeline and orchestration tools Experience designing and maintaining reliable batch and/or streaming pipelines using tools such as Airflow, dbt, Spark, Kafka, or equivalent modern data stack technologies. 5. Data warehouse / lakehouse architecture knowledge Strong understanding of modern data architecture concepts including data lakes, data warehouses, lakehouses, medallion-style layering, data quality, and scalable ingestion/serving patterns.

Good to Have Skills 1. Experience with big data / distributed processing frameworks Exposure to Spark, Databricks, Flink, or similar technologies for large-scale data transformation and processing. 2. Data governance and data quality practices Familiarity with lineage, cataloging, schema management, observability, data testing, and governance controls. 3. CI/CD and infrastructure-as-code for data platforms Experience with Git-based workflows, Terraform, Docker, Kubernetes, and deployment automation for data engineering solutions. 4. Streaming / real-time data experience Knowledge of event-driven architectures and real-time ingestion/processing using Kafka, Kinesis, Pub/Sub, or similar tools. 5. Business intelligence and analytics enablement Ability to work closely with analytics, product, and business teams to deliver curated datasets that support reporting, dashboards, and self-service analytics.