Big Data Technical Analyst at GVA Partners

Job Description

• A Big Data Technical Analyst proficient with Python, Apache Hadoop, Apache Cassandra and other Big Data and Enterprise Analytics tools is needed to join a dynamic team.

Responsibilities

• Designs, develops and tests new and/or existing data solutions running on the client's platforms.
• Analyzes technical and business requirements to develop a systems solution that aligns with enterprise best practices including user experience and accessibility.
• Utilizes agile software development practices, secure coding practices, code reviews, and software architecture.
• Uses knowledge of distributed computing techniques to design, develop and test scalable ETL/Processes that operate on large volume datasets.
• Familiar with handling datasets containing mixes of structured and unstructured data.
• Transforms unstructured data into suitable forms for analysis and modeling.
• Performs extract, transform and load (ETL) integrations with variety of data sources.
• Writes ad-hoc scripts and queries, schedules batch jobs and develops real-time streaming applications and monitors.
• Works with team to identify and build efficient and scalable processes.
• Be part of a development team to build and maintain the ETL processes
• Develop, test, debug, document and help operationalize various ETL applications leveraging industry best practices
• Work closely and collaborate with various cross-functional IT teams to identify, troubleshoot and fix data issues, and resolve data gaps that impact the fulfillment of the businessТs functional requirements

Qualification/ Experiences

• At least 3 years hands-on ETL experience
• Strong foundation in big data concepts - map-reduce, RDDs, batch and stream processing, data formats, ETL process flow
• Experience in Python programming.
• Proficient in Spark and Spark streaming architecture.
• Utilizes agile software development practices, secure coding practices, code reviews, and software architecture.
• Uses knowledge of distributed computing techniques to design, develop and test scalable applications that operate on large volume datasets.
• Familiar with handling datasets containing mixes of structured and unstructured data.
• Transforms unstructured data into suitable forms for analysis and modeling.
• Writes ad-hoc scripts and queries, schedules batch jobs and develops real-time streaming applications and monitors.
• Experience using Big Data based applications/tooling/languages such as Hadoop, Spark, Kafka, Hive, HBase.
• Hands-on telco experience.