Responsibilities:

* Design, develop, and maintain data pipelines using Spark, Python, Scala, and Java.

* Write efficient and optimized SQL queries for data extraction, transformation, and loading (ETL) processes.

* Work with DataFrames to manipulate and analyze large datasets.

* Implement data storage and processing solutions using cloud technologies (preferably AWS or GCP).

* Build and maintain real-time data streaming pipelines using MSK/Kafka.

* Utilize S3 for data storage and retrieval.

* Work with data lake technologies like Iceberg.

* Ensure data quality, integrity, and security.

* Collaborate with data scientists and other engineers to understand data requirements and deliver solutions.

* Participate in code reviews and contribute to improving our development processes.

* Troubleshoot and resolve issues in data pipelines and back-end systems.

Qualifications:

* Bachelor's degree in Computer Science or a related field (or equivalent experience).

* 5+ years of experience in back-end development with a focus on data engineering.

Required Skills:

* Strong proficiency in Spark, Python, Scala, and Java.

* Expertise in SQL and working with relational databases.

* Experience with DataFrames for data manipulation and analysis.

* Experience with cloud technologies (preferably AWS or GCP).

* Experience with message streaming platforms like MSK/Kafka.

* Experience with S3 or similar object storage.

* Experience with data lake technologies like Iceberg.

* Solid understanding of data warehousing concepts.

* Excellent communication and collaboration skills.

Bonus Points:

* Experience with data modeling and schema design.

* Experience with data governance and data quality management.

* Experience with DevOps practices and CI/CD pipelines.

* Relevant certifications (e.g., AWS Certified Data Engineer, Google Cloud Certified Professional Data Engineer).