Key skills
Amazon RedshiftApacheAWSCloudDistributed SystemsDockerETLKafkaKubernetesMicroservicesPySparkPythonPyTorchSparkTensorflowAIMachine LearningMLTensorFlowData EngineeringSnowflakeRedshiftApache SparkLambdaS3GlueAthenaPerformance OptimizationAgileCI/CD
About this role
Role Overview
- Design scalable data solutions and build robust pipelines.
- Integrate machine learning models into data workflows.
Requirements
- 3-6-years of hands-on experience in data engineering with a focus on ETL workflows, data pipelines, and cloud computing.
- Proven expertise or certification in Palantir Foundry is highly preferred.
- Strong experience with AWS services for data processing and storage (e.g., S3, Glue, Athena, Lambda, Redshift).
- Proficiency in programming languages such as Python, PySpark.
- Deep understanding of microservices architecture and distributed systems.
- Familiarity with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch) and their integration into data pipelines.
- Experience with big data technologies like Apache Spark, Kafka, and Snowflake.
- Strong problem-solving and performance optimization skills.
- Exposure to modern DevOps practices, including CI/CD pipelines and container orchestration tools like Docker and Kubernetes.
- Experience working in agile environments delivering complex data engineering solutions.
Tech Stack
- Amazon Redshift
- Apache
- AWS
- Cloud
- Distributed Systems
- Docker
- ETL
- Kafka
- Kubernetes
- Microservices
- PySpark
- Python
- PyTorch
- Spark
- Tensorflow
Benefits
- EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process.
- Has not authorized any agencies or partners to collect any fee or payment from prospective candidates.