
Senior Big Data Architect
2 days ago
We are seeking a seasoned data professional to join our team as an AWS Senior Data Engineer. In this role, you will be responsible for designing and implementing scalable big data solutions using Spark and AWS services.
The ideal candidate will have 7-9 years of IT experience with a strong background in AWS-related projects, including certifications like Associate and Professional Level AWS Certification. Proficiency in programming languages such as Scala, Python, and Shell Scripts is essential.
- Key Responsibilities:
- Develop and implement scalable Spark jobs using Scala for new project requirements.
- Optimize Spark job performance through stress testing and tuning.
- Design efficient data pipelines using AWS Lambda or Apache Airflow for developed/enhanced Spark jobs.
- Analyze data processing, integration, modeling, and reporting requirements to define data loading strategies.
- Balance cost and performance optimally.
- 7-9 years of IT experience with 5+ years in AWS-related projects.
- Associate and Professional Level AWS Certification is a plus.
- Proficiency in AWS Services: 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 Linux flavor, Windows.
- Strong SQL skills are essential.
- Orchestration Tools: Apache Airflow.
- Expertise in ETL workflows with complex transformations.
- Understanding of AWS VPC, Subnets, Security Groups, and Route Tables.
As a member of our team, you will have the opportunity to work on exciting projects, collaborate with experienced professionals, and grow your skills in a fast-paced environment.
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