
Apply Now Senior Data Engineer
1 week ago
Job Summary:
We are seeking an experienced Data Engineer with strong expertise in AWS cloud services and Databricks to design and implement scalable, high-performance data pipelines. The role involves building and optimizing ETL/ELT workflows, managing big data environments, and ensuring seamless data availability for analytics, AI/ML, and business intelligence use cases.
Key Responsibilities:
- Design, develop, and maintain data pipelines and workflows using AWS (S3, Redshift, Glue, EMR, Lambda, Kinesis, Athena) 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).
Preferred Qualifications:
- 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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