Big Data Engineering Specialist
23 hours ago
We are seeking a seasoned professional to lead our big data engineering efforts, leveraging expertise in cloud-based architectures and scalable data pipelines.
- Drive the design and implementation of high-performance data processing systems using Spark, ensuring optimal cost and performance balance.
- Analyze existing data integration frameworks and assess their impact on new requirements, identifying opportunities for improvement.
- Develop efficient data pipelines for developed/enhanced Spark jobs using AWS Lambda or Apache Airflow, considering volume, data types, frequency, and analytics specifications.
- Create databases with logical and physical designs, star schema, and snowflake schema, ensuring data consistency and integrity.
- Work closely with project managers to ensure successful project delivery, providing estimation, scoping, scheduling assistance, and quality assurance.
Technical Requirements:
- 7-9 years of IT experience, with at least 5 years in AWS-related projects.
- Associate Level and Professional Level AWS Certification (good to have).
- In-depth knowledge of AWS Services, including S3, EC2, EMR, Serverless, Athena, AWS Glue, Lambda, Step Functions.
- Cloud Databases: AWS Aurora, Singlestore, RedShift, Snowflake.
- Big Data: Hadoop, Hive, Spark, YARN.
- Programming Languages: Scala, Python, Shell Scripts, PySpark.
- Operating Systems: Any flavor of Linux, Windows.
- Strong SQL Skills.
- Orchestration Tools: Apache Airflow.
- ETL workflow expertise with complex transformations like SCD, deduplications, aggregations.
- Conceptual understanding of AWS VPC, Subnets, Security Groups, & Route Tables.
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