Data Integration Engineer

Title: Data Integration Engineer

Duration: 1+ Year Contract

Location: 100% REMOTE Work

Rate: $Open/hr.

Responsibilities

• Develop, test, document and maintain scalable data pipelines.
• Build out new data integrations including APIs to support continuing increases in data volume and complexity.
• Establish and follow data governance processes and guidelines to ensure data availability, usability, consistency, integrity, and security.
• Build and implement scalable solutions that align to our data governance standards and architectural road map for data integrations, data storage, reporting, and analytic solutions.
• Collaborate 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.
• Design and develop data integrations and a data quality framework. Write unit/integration/functional tests and document work.
• Design, implement, and automate deployment of our distributed system for collecting and processing streaming events from multiple sources
• Perform data analysis required to troubleshoot data-related issues and assist in the resolution of data issues.
• Guide and mentor less experienced engineers on coding best practices and optimization.

Qualifications:

• Education: 4-year college degree or equivalent combination of education and experience. Prefer academic background in in Computer Science, Mathematics, Statistics, or related technical field.
• 7 years of relevant work experience in analytics, data engineering, business intelligence or related field.
• Skilled in object-oriented programming (Python in particular).
• Experience developing integrations across multiple systems and APIs.
• Experience with or knowledge of Agile software development methodologies.
• Experience with cloud-based databases, specifically AWS technologies (e.g. Redshift, RDS, S3, EMR, EC2, Kinesis).
• Experience using SQL queries as well as writing and optimizing SQL queries in a business environment with large-scale, complex datasets.
• Experience with data warehouse technologies. Experience creating ETL and/or ELT jobs.
• Excellent problem solving and troubleshooting skills.
• Process oriented with great documentation skills.
• Experience developing in a Linux environment.
• Experience designing data schemas and operating SQL/NoSQL database systems is a plus.
• Experience with Big Data tools like Spark, Hadoop, Kafka, etc. is a plus.