We are seeking a highly skilled and motivated Data Engineer to join our dynamic team. As a Data Engineer, you will collaborate closely with our Data Scientists to develop and deploy machine learning models. Proficiency in below listed skills will be crucial in building and maintaining pipelines for training and inference datasets.
Work in tandem with Data Scientists to design, develop, and implement machine learning pipelines.
Utilize PySpark for data processing, transformation, and preparation for model training.
Leverage AWS EMR and S3 for scalable and efficient data storage and processing.
Implement and manage ETL workflows using Stream sets for data ingestion and transformation.
Design and construct pipelines to deliver high-quality training and inference datasets.
Collaborate with cross-functional teams to ensure smooth deployment and real-time/near real-time inferencing capabilities.
Optimize and fine-tune pipelines for performance, scalability, and reliability.
Ensure IAM policies and permissions are appropriately configured for secure data access and management.
Implement Spark architecture and optimize Spark jobs for scalable data processing.
Proficiency in Advanced SQL (Window functions), Spark Architecture, Pyspark or Scala with Spark, Hadoop.
Proven expertise in designing and deploying data pipelines.
Strong problem-solving skills and ability to work effectively in a collaborative team environment.
Excellent communication skills and ability to translate technical concepts to non-technical stakeholder
Hands-on experience with Airflow, S3, and Stream sets or similar ETL tools. [ can be trained locally ]
Understanding of real-time or near real-time inferencing architectures.
Basic Knowledge on Kafka ,AWS IAM, AWS EMR and Snowflake.
Screening Criteria:
Immediate joiners -15 Days
Strong in communication
Location:Chennai / Noida
Duration: 6-12 Months
Qualifications:
Any Degree
Primary skills (Must have):
SQL
Spark Architecture,
Pyspark or Scala
Spark
Hadoop
Airflow
ETL tools.
Secondary Skills:
Understanding of real-time or near real-time inferencing architectures.
