Design, build, and maintain robust and scalable data pipelines using tools such as Apache Airflow, Python and SQL
Develop, build, Dashboard , Report using BI Tools : Looker, Looker Studio, Power BI, Metabase
Develop and optimize data architecture and data models to support business intelligence, analytics needs
Collaborate with business user, data scientists, analysts, and software engineers to understand data requirements and ensure smooth data flow
Implement data quality checks, logging, monitoring, and alerting for pipeline healthManage and optimize cloud-based data infrastructure (e.g., GCP, AWS, or Azure)
Ensure data governance, security, and compliance best practices are followed
Mentor junior data engineers and contribute to knowledge sharing within the team
Stay up-to-date with industry best practices and emerging technologies in big data and analytics
Requirements
Person We Are Looking For
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
Min. 4 years of experience in data engineering
Strong proficiency in SQL and PythonExperience with modern data tools and frameworks: Spark, Airflow, Kafka, DBT, etc
Hands-on experience with cloud platforms (e.g., GCP BigQuery, AWS Redshift, or Azure Synapse)
Deep understanding of data modeling, ETL/ELT design, and data warehousing concepts
Has experience in migration datawarehouse from onpremise to cloud is a plus
Solid grasp of CI/CD and DevOps practices for data systems
Strong problem-solving and communication skills
Certified Data Engineer Professional at any cloud is a plus
