Source description
About the role
Technical Must Haves:
Must have high level skills in Python and Spark.
Proficient with AWS EMR, SQS, Lambda, and Step Functions.
Strong preference for experience with Databricks, Dremio and Scala, and Java.
Soft Skill Must Haves:
Independent, doesn't need to be micro managed.
Good verbal communication skills.
Required Skills:
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Strong hands on experience building ETL pipelines using Apache Spark.
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Hands on experience with AWS services such as Glue, EMR, Lambda, Step Functions, CloudTrail, CloudWatch, SNS, SQS, S3, VPC, EC2, RDS, IAM.
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Proficient in Python and/or Scala programming languages
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Knowledge of application development lifecycles, & continuous integration/deployment practices
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Experience with development on AWS and cloud native applications
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Experience with S3, DynamoDB, Kinesis and Snowflake
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Experience with Developing Data Platforms on AWS
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Proficient in Agile Software Development methodology, processes, and practices.
Qualifications
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Bachelors degree in related field
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Strong, analytical, focused, self-driven with excellent problem-solving skills
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Minimum 5 years of hands on in-depth experience of AWS Data Pipelines development and implementation is required
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AWS Associate or Professional level certifications is a plus
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