Job Profile - Data Engineer
Positions: 8
Location - Onsite
Role - Contract
Minimum Skills Required:
Bachelor's degree (typically in Computer Science, Management Information Systems, Mathematics, Business Analytics or another technically strong program), plus 2 years of experience
Proven Big Data technology development experience including Hadoop, Spark (PySpark), and Hive
Understanding of Agile Principles (Scrum)
Experience developing with Python
Cloud Development (Azure)
Exposure to VCS (Git, SVN) Position Specific Skill Preferences:
Experience developing with SQL (Oracle, SQL Server)
Exposure to NoSQL (Mongo, Cassandra)
Apache NiFi
Airflow
Docker Key Responsibilities
Innovate, develop, and drive the development and communication of data strategy and roadmaps across the technology organization to support project portfolio and business strategy
Drive the development and communication of enterprise standards for data domains and data solutions, focusing on simplified integration and streamlined operational and analytical uses
Drive digital innovation by leveraging innovative new technologies and approaches to renovate, extend, and transform the existing core data assets, including SQL-based, NoSQL-based, and Cloud-based data platforms
Define high-level migration plans to address the gaps between the current and future state, typically in sync with the budgeting or other capital planning processes Lead the analysis of the technology environment to detect critical deficiencies and recommend solutions for improvement
Mentor team members in data principles, patterns, processes and practices
Promote the reuse of data assets, including the management of the data catalog for reference
Draft and review architectural diagrams, interface specifications and other design documents
Proactively and holistically lead activities that create deliverables to guide the direction, development, and delivery of technological responses to targeted business outcomes.
Provide facilitation, analysis, and design tasks required for the development of an enterprise's data and information architecture, focusing on data as an asset for the enterprise.
Develop target-state guidance (i.e., reusable standards, design patterns, guidelines, individual parts and configurations) to evolve the technical infrastructure related to data and information across the enterprise, including direct collaboration with 84.51.