Associate Staff Engineer, Big Data Engineer

• Total experience 5+years.
• Hands on experience in Data Engineering, Data Lakes, Data Mesh, or Data Warehousing/ETL environments.
• Strong working knowledge in Python, SQL, Airflow and PySpark.
• Hands-on experience implementing projects applying SDLC practices.
• Hands on experience in building data pipelines and building data frameworks for unit testing, data lineage tracking, and automation.
• Experience with building and maintaining a cloud system.
• Familiarity with databases like DB2 and Teradata.
• Strong working knowledge in Apache Spark, Apache Kafka, Hadoop and MapReduce.
• Strong troubleshooting skills and ability to design for scalability and flexibility.
• Expertise in Spanner for high-availability, scalable database solutions.
• Knowledge of data governance and security practices in cloud-based environments.
• Problem-solving mindset with the ability to tackle complex data engineering challenges
• Familiar with containerization technologies (Docker/Kubernetes).
• Excellent communication and collaboration skills.

RESPONSIBILITIES:

• Writing and reviewing great quality code.
• Understanding the client s business use cases and technical requirements and be able to convert them in to technical design which elegantly meets the requirements
• Mapping decisions with requirements and be able to translate the same to developers
• Identifying different solutions and being able to narrow down the best option that meets the client s requirements.
• Defining guidelines and benchmarks for NFR considerations during project implementation
• Writing and reviewing design documents explaining overall architecture, framework, and high-level design of the application for the developers
• Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
• Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
• Understanding and relating technology integration scenarios and applying these learnings in projects.
• Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken
• Carrying out POCs to make sure that suggested design/technologies meet the requirements.