AWS Data Engineer with Hadoop experience

SUMMARY:
Design, build and operationalize large scale enterprise data solutions and applications using one or

POSITION INFO:

Job Description

Responsibilities:

• Design, build and operationalize large scale enterprise data solutions and applications using one or more of AWS data and analytics services in combination with 3rd parties - Spark, EMR, DynamoDB, RedShift, Kinesis, Lambda, Glue, Snowflake.
• Analyze, re-architect and re-platform on-premise data warehouses to data platforms on AWS cloud using AWS or 3rd party services.
• Design and build production data pipelines from ingestion to consumption within a big data architecture, using Java, Python, Scala.
• Design and implement data engineering, ingestion and curation functions on AWS cloud using AWS native or custom programming.
• Perform detail assessments of current state data platforms and create an appropriate transition path to AWS cloud.
• Design, implement and support an analytical data infrastructure providing ad-hoc access to large datasets and computing power.
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies.
• Creation and support of real-time data pipelines built on AWS technologies including Glue, Redshift/Spectrum, Kinesis, EMR and Athena
• Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency
• Working closely with team members to drive real-time model implementations for monitoring and alerting of risk systems.
• Collaborate with other tech teams to implement advanced analytics algorithms that exploit our rich datasets for statistical analysis, prediction, clustering and machine learning
• Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers

Qualifications

• Bachelor''s Degree in Computer Science, Information Technology or other relevant fields
• Has experience in any of the following AWS Athena and Glue Pyspark, EMR, DynamoDB, Redshift, Kinesis, Lambda, Snowflake
• Proficient in AWS Redshift, S3, Glue, Athena, DynamoDB, EMR
• Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations

Work Experience

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
• Experience working with distributed systems as it pertains to data storage and computing
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, meta data, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected data sets.
• Working knowledge of message queuing, stream processing, and highly scalable Big Data, data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Experience in a Data Engineer or similar roles
• Experience with big data tools is a must: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc

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