Intermediate Data Engineer developing solutions for big data reporting and analytics. Collaborating with stakeholders to deliver precision reporting and performance measurement for the organization.
Responsibilities
Working in collaboration with customers across the organization (Strategic Analytics, Claims, Insurance, Finance, Driver Licensing, Road Safety, etc.) to plan, scope, execute and sustain data-based solutions.
Responding to internal and external ad hoc requests, review and clarify data requirements, ensuring report content is acceptable within policy and privacy protocols.
Providing subject matter expertise within the department and to clients on data sources, reporting workflows, business process, and the appropriate tools with which to analyze their data.
Participating with corporate data user teams, developing data validation and test plans, performing user acceptance testing, and providing feedback to development and sustainment teams.
Conducting analysis for moderate to complex requests, defining data fields and determining data availability, developing information layout, format and interactivity. Presenting findings and providing clarification.
Requirements
Advanced skill in Object Oriented programming languages such as Scala, Python or Java.
Working experience with Big Data platforms, with exposure to Hadoop ecosystem (Spark, HDFS, Hive, Kafka) and AWS big data technologies (AWS Glue, Lamba, and S3)
Experience with CI/CD tools like Jenkins, Git, Fisheye, SVN
Experience in developing efficient and robust data transformation & ingestion pipelines
Working experience in building and deploying machine learning models.
Advanced working SQL knowledge and experience working with Relational and NoSQL databases.
Strong analytical skills related to working with unstructured datasets.
Demonstrated ability to work with large and complex datasets, while managing priorities and responding to time pressures.
Detail-oriented with demonstrated ability to meet deadlines, manage multiple priorities and work effectively under pressure.
Strong data quality management process understanding, data analysis and data profiling.
Ability to apply critical thinking skills to troubleshoot and perform root cause analysis on technical problems and solution design.
Providing technical advice and guidance to staff in resolving complex data ingestion and transformation issues.
Experience with performance tuning and code optimization.
Design, develop and enforce best practices and standards around data engineering.
Ability to work effectively with a team or independently, as well as lead small teams as needed.
Demonstrating leadership qualities in coaching junior staff members and new hires.
Understanding of Agile Methodologies.
Excellent interpersonal, verbal and written communication skills to work with Managers, Directors and Executive level stakeholders.
Experience with reporting and visualization tools, such as Tableau, user interface design, and iterative customer-driven design processes would be additional assets.
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