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Chief Data Systems Architect
3 weeks ago
We are seeking an experienced data engineer to lead the design and implementation of scalable, high-performance data pipelines using cloud services and big data environments.
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:
- 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).
Benefits of a Successful Candidate
- 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.
A successful candidate will have a deep understanding of data engineering principles and a passion for building scalable, efficient, and effective data systems.
