
Cloud Data Architect
23 hours ago
As a Data Engineer, you will play a pivotal role in designing and building robust data pipelines that power our cloud-native solutions.
Our ideal candidate will have hands-on experience in building data pipelines and cloud-based data solutions, with a strong focus on developing efficient ETL/ELT workflows.
- Key Responsibilities:
- Design and develop scalable data infrastructure to support AI-driven workflows and applications.
- Leverage AWS services such as S3, Glue, EMR, Lambda, Kinesis, Step Functions, Redshift, Athena, DynamoDB, RDS, and Lake Formation for data ingestion, transformation, storage, and querying.
- Ensure robust data governance, security, and quality controls throughout the data lifecycle.
- Collaborate closely with AI/ML teams to prepare clean, high-quality datasets optimized for model training, inference, and fine-tuning.
- Implement CI/CD pipelines and data engineering best practices in a cloud-native architecture for automated deployments.
- Monitor, debug, and resolve issues in data pipelines to ensure high availability, reliability, and minimal latency.
- Requirements:
- 3–7 years of hands-on experience in Data Engineering and building data pipelines.
- Strong programming skills in Python, SQL, and/or Scala/Java.
- Expertise in AWS cloud services, including S3, Glue, EMR, Redshift, Athena, Kinesis, Lambda, Step Functions, DynamoDB, and RDS.
- Experience with data pipeline orchestration tools such as Apache Airflow, AWS Step Functions, Dagster, or similar.
- Proficiency in big data frameworks like Apache Spark, Hadoop, or Flink.
- Why Join Us:
- Collaborative, cross-functional team environment.
- Opportunities for growth and professional development.
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