Principal Data Engineer

Lets do this. Lets change the world. In this vital role you will serve a critical function within Organizational, Planning, Analytics & Insights with a goal of enterprise-wide, long-term workforce transformation by connecting people, financial, procurement & capability data to enable business insights & decisions. The Principal Data Engineer will collaborate with the Tech and Data lead for OPA&I and will be responsible for architecture and quality of the OPA&I data systems.

• Data Integration and Management: Lead the design, development and management of data infrastructure related to organizational planning. Develop and maintain robust data pipelines to integrate data from various sources including HR, Finance, Procurement, and Activities. Ensure seamless data flow and synchronization between different systems and databases. Implement strategies and tools to efficiently run and process unstructured data. Develop methods for extracting important insights from unstructured data sources. Establish and implement data validation procedures to ensure data accuracy and consistency. Develop and maintain data standards and ensure data integrity across all systems. Develop and maintain a single source of truth for organizational data. Be responsible for the development and maintenance of a single source of truth for organizational data.
• Automation development: Design and implement automation solutions for data processes, including one-click baselining and case generation. Continuously seek opportunities to improve efficiency through automation. Lead the development and implementation of automation solutions for data processes. Ensure automation initiatives enhance efficiency and support strategic business goals.
• Process and Data Improvement: Identify and implement improvements in data processes and workflows. Collaborate with other teams to enhance data quality and operational efficiency. Monitor and optimize data systems for performance, scalability, and security. Stay updated with the latest industry trends and advancements in software architecture and development. Find opportunities for process improvements and drive initiatives to enhance the efficiency of the development lifecycle.
• Leadership: Provide strategic leadership in designing and implementing system architecture to support business objectives. Architect, design, and implement scalable and efficient data pipelines and systems. Develop and maintain data architecture solutions to support analytics reporting. Ensure data infrastructure is robust, secure, and optimized for performance. Facilitate technical discussions and decision-making processes within the team. Be an interdisciplinary team member who is innovative, accountable, reliable, and able to thrive in a constantly evolving environment. Provide technical guidance and mentorship to junior data engineers. Lead architectural reviews and ensure consistency to best practices in data engineering. Ensures data quality and operational expectations of the data systems.

• Masters degree in computer science or engineering field plus 8 to 10 years of relevant experience OR
• Bachelors degree in computer science or engineering field plus 10 to 14 years of relevant experience OR
• Diploma and Minimum of 12+ years of relevant work experience

• 6+ years of development experience with Databricks (or Snowflake), including cluster setup, execution, and tuning
• Experience building ETL or ELT pipelines; Hands-on experience with SQL/NoSQL
• Experience with one or more programming languages, Python, R, SAS, Scala, or Java.
• Experience with common data processing libraries: Pandas, PySpark, SQLAlchemy.
• Experience with software engineering best-practices, including but not limited to version control, infrastructure-as-code, CI/CD, and automated testing
• Experience with data lake, data fabric and data mesh concepts
• Experience with data modeling, performance tuning, and experience on relational and graph databases
• Experience directing technical team to define scope, allocate work and provide technical guidance
• Experience working in Agile-based teams
• Experience operationalizing and running production data systems: Airflow, Linux, Monte Carlo, Kafka.
• Experience with cloud engineering in AWS, Azure or GCP
• Experience with DevOps tools (Ansible/ Gitlab CI/CD / GitHub / Docker /Jenkins)
• Experience as an architect leading the design and implementation of data systems

• Experience with AWS services: EC2, S3, EMR, RDS, Redshift/Spectrum, Lambda, Glue, Athena, API gateway, and design patterns (Containers, Serverless, Kubernetes, Docker, etc.)
• Experience building and maintaining operationalized REST API endpoints for data integration

Professional Certifications:

• Databricks (preferred)
• Cloud Engineer AWS / Azure / GCP (preferred)

• Excellent analytical and solving skills
• Strong verbal and written communication skills
• Ability to work effectively with global, virtual teams
• High degree of initiative and self-motivation
• Ability to manage multiple priorities successfully
• Team-oriented, with a focus on achieving team goals
• Strong presentation and public speaking skills