Data Engineer

Roles & Responsibilities • Design, build, and maintain scalable and reliable data pipelines to support analytics, ML models, and business reporting.

• Collaborate with data scientists and analysts to ensure data is available, clean, and optimized for downstream use.

• Implement data quality checks, monitoring, and validation processes.

• Design efficient ETL/ELT workflows and integrate multiple data sources (databases, APIs, third-party tools) into centralized storage (data lakes/warehouses).

• Support cloud-based infrastructure for data storage and retrieval.

• Monitor, troubleshoot, and optimize existing pipelines for large-scale, real-time data flows.

• Apply best practices for query optimization and cost-efficient storage.

• Partner with product, engineering, and business stakeholders to gather requirements.

• Document workflows, schemas, and processes while supporting a culture of reliability, governance, and security. Requirements: • Proficiency in Python and SQL for data engineering tasks.

• Strong understanding o f ETL/ELT processes, data warehousing, and data modeling.

• Hands-on experience with cloud platforms (AWS, GCP, or Azure) and data storage solutions (BigQuery, Redshift, Snowflake, etc.).

• Familiarity with data orchestration tools Airflow, Airbyte is a must .

• Experience with containerization & deployment tools (Docker, Kubernetes) is a plus.

• Knowledge of data governance, security , and best practices for handling sensitive data.Familiarity to work with Git and GitHub.

• Dataform is a must

• Strong skills in eliciting requirements from cross-functional stakeholders and translating them into actionable data engineering tasks. Experience: • Preferably total 4 years of experience

• 2+ years in data engineering , building and maintaining data pipelines.

• 2+ years of SQL and Python development in production environments.

• Experience working in Fast-growing startup environments is a plus.

• Exposure to real-time data processing frameworks (Kafka, Spark, Flink) is a plus.