Senior Data Engineer (Big Data & AWS)

Experience:

8–12 years of experience in designing and building high-volume, high-performance data pipelines

Education:

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field

Design, develop, and deploy scalable data solutions
Work on high-volume data processing within Big Data and AWS ecosystems
Collaborate with cross-functional teams to support business and product use cases

Collaborate with Data & Analytics teams to gather technical requirements
Build and maintain scalable ETL pipelines on Big Data / Cloud platforms
Handle data collection, storage, processing, and transformation of large datasets
Solve complex data engineering problems and improve architecture
Support production issues related to application functionality and integrations

Strong communication skills (verbal and written)
Expertise in Big Data and Cloud data ecosystems
Experience in building high-volume data pipelines using Spark / Big Data technologies
Strong programming skills in Python / Scala
Advanced SQL skills with ability to write complex and efficient queries
Hands-on experience with AWS Data Stack:
S3, AWS Glue, Lambda, Athena, Redshift, EMR
Experience in building Data Lakes
Exposure to real-time/streaming data processing:
Kafka, Spark Streaming, AWS Kinesis
Strong understanding of Data Warehouse concepts
Experience in data modelling and database design (Data Lake preferred)
Strong analytical and problem-solving skills
Ability to manage multiple tasks under tight deadlines

Big Data Engineer (Scala, AWS)