Data Engineer

Our Financial client is looking for a Data Engineer

• Develops and maintain scalable data pipelines
• Build out new API integrations to support continuing increases in data volume and complexity.
• Work on Apache NiFi an ETL tool with flow-based programming that comes with a web UI built to provide an easy way (drag & drop) to handle data flow in real-time. This also supports powerful and scalable means of data routing and transformation, which can be run on a single server or in a clustered mode across many servers.
• builds data processing frameworks that handle the business's growing database.
• Collaborates with analytics and business teams to improve data models that feed business intelligence tools increasing data accessibility and fostering data-driven decision making across the organization.
• Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Writes unit/integration tests, contributes to engineering wiki, and documents work.
• Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
• Works closely with a team of frontend and backend engineers, product managers, and analysts.
• Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models.
• Designs data integrations and data quality framework.
• Designs and evaluates open source and vendor tools for data lineage.
• Works closely with all business units and engineering teams to develop strategy for long term data platform architecture.

Qualifications / Skills:

• Experience with or knowledge of Agile methodologies
• Excellent problem solving and troubleshooting skills
• Process oriented with great documentation skills
• Excellent oral and written communication skills with a keen sense of customer service

Requirements:

• Must t have had at least 5 years of working experience working in a data engineering department, preferably as a Data Engineer in a fast-paced environment and complex business setting. Experience working with varied forms of data infrastructure inclusive of relational databases such as SQL, Hadoop, Spark, NIFI and column-oriented databases such as Redshift, MySQL, and Vertica.