Sr AWS Cloud Engineer

Responsibilities:

• Collaborate as part of a development team to design and enhance large scale applications developed using Python, Spark.
• Evaluates and plans software designs, test results and technical manuals using AWS
• Confer with business units and development staff to understand both the business and technical requirements for producing technical solutions.
• Create and review technical and user-focused documentation for data solutions (data models, data dictionaries, business glossaries, process and data flows, architecture diagrams, etc.).
• Extend and enhance the business Data Lake
• Create or implement solutions for metadata management
• Solve for complex data integrations across multiple systems.
• Design and execute strategies for real-time data analysis and decisioning.
• Build robust data processing pipelines using AWS Services and integrate with multiple data sources
• Translating client user requirements into data flows, data mapping, etc.
• Analyses and determines data integration needs and follows Agile practices.

• At least 5+ years of experience on designing and developing Data Pipelines for Data Ingestion or Transformation using Scala or Python
• At least 4 years of experience with Python, Spark.
• At least 3 years of experience working on AWS technologies.
• Experience of designing, building, and deploying production-level data pipelines using tools from AWS Glue, Lamda, Kinesis using databases Aurora and Redshift.
• Experience with Spark programming (pyspark or scala).
• Hands on experience with AWS components like (EMR, S3, Redshift, Lamdba, API Gateway, Kinesis ) in production environments
• Strong analytical skills and advanced SQL knowledge, indexing, query optimization techniques.
• Experience using ETL tools for data ingestion..
• Experience with Change Data Capture (CDC) technologies and relational databases such as MS SQL, Oracle and DB
• Ability to translate data needs into detailed functional and technical designs for development, testing and implementation

• 5+ Years of Development / Data Engineering Experience

• 4+ Years Developing with AWS Cloud solutions

• 4+ Years Developing in Spark/PySpark

• 4+ Years Developing AWS Glue ETL

• 4 + Years AWS Storage models (S3 and DynamoDB)

• Some hands-on developing with on-prem ETL tooling (Ab Initio preferred, Informatica)

Additional Skills:

• Strong experience in AWS GLUE, EMR, Hudi, experience extracting data from multiple sources & loading data into Data Lakes, AWS Redshift
• Experience working with AWS Elastic search, RDS, PostgreSQL preferred
• Experience w/ AWS services such as Lambda, EMR, SNS/SQS, Event Bridge, Lake Formation & Athena
• Experience w/ integrating applications/systems (data producers) with Enterprise Kafka topics (Confluent Kafka integration w/ AWS S3, Redshift)
• Experience in Requirements Analysis, Data Analysis, Application Design, Application Development & Integration Testing
• Working knowledge of on-prem Extraction, Transformation, Cleansing and Loading methodology and principles
• Experience implementing and adding to DevOps principles (GitLab, maintaining CI/CD pipelines)
• Experience in Java svcs is nice to have