Python/Pyspark Data Engineer
Python/Pyspark Data Engineer ( Must have Databricks Exp )
Jersey City, NJ (Hybrid 3 Days a Week)
12+ Months
Must have 10+ Years experience
Job responsibilities
experience in public cloud migrations of complex systems, anticipating problems, and finding ways to mitigate risk, will be key in leading numerous public cloud initiatives
Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
end-to-end platform issues & help provide solutions to platform build and performance issues on the AWS Cloud & ensure the deliverables are bug free Drive, support, and deliver on a strategy to build broad use of Amazon's utility computing web services (e.g., AWS EC2, AWS S3, AWS RDS, AWS CloudFront, AWS EFS, AWS DynamoDB, CloudWatch, EKS, ECS, MFTS, ALB, NLB) Design resilient, secure, and high performing platforms in Public Cloud using company best practices
Duties and responsibilities
● Collaborate with the team to build out features for the data platform and consolidate data assets
● Build, maintain and optimize data pipelines built using Spark
● Advise, consult, and coach other data professionals on standards and practices
● Work with the team to define company data assets
● Migrate CMS’ data platform into Chase’s environment
● Partner with business analysts and solutions architects to develop technical architectures for strategic enterprise projects and initiatives
● Build libraries to standardize how we process data
● Loves to teach and learn, and knows that continuous learning is the cornerstone of every successful engineer
● Has a solid understanding of AWS tools such as EMR or Glue, their pros and cons and is able to intelligently convey such knowledge
● Implement automation on applicable processes
Mandatory Skills:
● 5+ years of experience in a data engineering position
● Proficiency is Python (or similar) and SQL
● Strong experience building data pipelines with Spark
● Strong verbal & written communication
● Strong analytical and problem solving skills
● Experience with relational datastores, NoSQL datastores and cloud object stores
● Experience building data processing infrastructure in AWS
● Bonus: Experience with infrastructure as code solutions, preferably Terraform
● Bonus: Cloud certification
● Bonus: Production experience with ACID compliant formats such as Hudi, Iceberg or Delta Lake
● Bonus: Familiar with data observability solutions, data governance frameworks
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