Key Responsibilities:
As a part of the Data and Analytics team, the Senior Data Engineer will provide critical strategic and analytical support to its portfolio companies and will be responsible for building and maintaining the vast ecosystem of data and analytics. Given the rapid pace of change in the data and analytics field, the Senior Data Engineer will also be a key technical visionary, helping the company find new efficiencies using technology by building a deep understanding of companies and processes, continually staying informed with developments in the data and analytics space, and assessing the application of new technology to the business. Key responsibilities for this highly visible and impactful position include:
- Identifying, implementing, and managing efficient, scalable, and reliable data pipelines and monitoring systems
- Developing deep intuition for its platform investments' data to rapidly create new data assets or augment existing assets to give business insight into key operational areas
- Identifying and implementing operational efficiencies through automation and/or integration
- Building end-user experiences to allow for self-service Business Intelligence (BI) across a variety of technical experience levels
- Uncovering new insights by mining data warehouse and putting
- Developing vision for future of data and analytics, building roadmaps to realize vision, and implementing projects to accomplish goals
- Insisting on the highest data integrity and establishing scalable quality checks and controls.
- Maintaining crisp data documentation to enable data accessibility to users of all technical competencies
- Managing GCP's data catalog and ensuring robust data discoverability for all end users
- Developing training materials and monitoring engagement to maximize impact
- Providing ad hoc analytical support and financial analyses to support strategic decision-making and financial planning activities
- Performs other duties as assigned
Experience and Qualifications:
- BS/MS in Computer Science, Information Systems, Data & Analytics or a related field
- Advanced SQL skills and experience scripting for automation (e.g., Python)
- Exceptional data modeling skills with deep understanding of various modeling approaches
- Experience developing batch and real-time data pipelines using tools like NiFi, Airflow, RabbitMQ, dbt, SQLMesh, etc.
- Experience working with modern cloud data platforms like AWS, Azure, GCP, Snowflake, etc.
- Experience sourcing and modeling data from third-party APIs
- Experience with data visualization tools like Power BI or Tableau
- Experience using git for version control and experience using GitHub to manage CI/CD pipelines
- Knowledge of machine learning libraries, i.e, scikit-learn, pytorch, and MLOps infrastructure like feature stores, monitoring tools, and model registries
- Excellent communication skills; able to communicate highly technical solutions to non-technical audiences
- Exceptionally organized and detail-oriented with the ability to work efficiently and accurately under pressure in a fast-paced environment
- Ability to work independently with limited supervision
- Curious spirit and continuous learner; ability to distinguish between fads and trends in data technology
- Collaborative nature and a good team player
- Experience with financial planning systems Vena, Planful, Workday, Hyperion, etc. is a plus
- Experience with Big Data technologies such as Spark/PySpark, Hive, Pig, and Kafka is also a plus