
Big Data Specialist
1 day ago
Our organization seeks an experienced data engineer to design and implement scalable, high-performance data pipelines using AWS cloud services and Databricks. The ideal candidate will have a strong understanding of big data frameworks, data warehousing, and data modeling.
Job Summary:
The data engineer will be responsible for designing, developing, and maintaining data pipelines and workflows using AWS (S3, Redshift, Glue, EMR, Lambda, Kinesis, Athena) and Databricks. This includes building and optimizing ETL/ELT processes for large-scale structured and unstructured datasets.
Key Responsibilities:
Design, develop, and maintain data pipelines and workflows using AWS and Databricks.Build and optimize ETL/ELT processes for large-scale structured and unstructured datasets.Leverage Databricks for data engineering, advanced analytics, and machine learning workloads.Collaborate with data scientists, analysts, and stakeholders to deliver reliable and scalable data solutions.Implement data governance, quality checks, and monitoring frameworks.Ensure high availability, scalability, and cost-effectiveness of data solutions.Required Skills:
The successful candidate will possess the following skills:
- 7+ years of experience in data engineering.
- Strong hands-on experience with AWS cloud services (S3, Redshift, Glue, EMR, Athena, Lambda, Kinesis).
- Expertise in Databricks (PySpark, Delta Lake, ML pipelines).
- Proficiency in Python and SQL for data transformation and querying.
- Strong understanding of data warehousing, data modeling, and big data frameworks.
- Experience with workflow orchestration tools (Airflow, Step Functions).
Preferred Qualifications:
The following qualifications are desirable:
- Familiarity with MLOps/ML integration within Databricks.
- Experience with real-time/streaming data (Kafka, Spark Streaming).
- Knowledge of infrastructure as code (Terraform/CloudFormation).
- Exposure to data security, compliance, and governance practices.
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