Manager, Data Engineering at Blackbaud
Data Engineering at Blackbaud is responsible for ingestion, transformation and integration of data in Blackbaud’s Data Platform. This scalable and performant big data platform supports data science, data enrichment, research and data analysis as well as making data operationally able to be consumed by Blackbaud’s products and services.
The Data Engineering Manager facilitates this by helping their teams’ take on large, complex data problems/initiatives and eliciting considerable technical influence within Data Engineering and the Data Intelligence Center of Excellence at Blackbaud. The Data Engineering Manager has a wide-ranging experience and extensive knowledge in major parts of our data platform and data engineering tech stack, serving as strategy and process owner of significant components of our data architecture. This role provides high-level guidance, team mentoring, coaching and influencing technical direction within the Data Engineering teams. They are also creativity leaders, finding alternatives and new approaches to difficult problems and application of data and insight.
In addition to the team management responsibilities this role will help craft the vision for how Blackbaud’s Data Strategy helps nonprofit organizations be more effective raising money and facilitating their visions.
What will I be doing?
- Develop and direct the strategy for all aspects of Data Engineering
- Set, communicate and facilitate technical direction more broadly for the Data Intelligence Center of Excellence and collaboratively beyond the Center of Excellence
- Keep current on technology: distributed computing, big data concepts and architecture.
- Define the tools and pipeline patterns our data engineers use to transform data and support our data science practice
- Lead teams that design and implement pipelines that support data ingestion, data movement, transformation, aggregation, machine learning, data science, and much more.
- Design and develop breakthrough products, services or technological advancements in the Data Intelligence space that expand our business
- Work alongside product management to craft technical solutions to solve customer business problems.
- Set and achieve annual and quarterly Objectives and Key Results (OKRs)
- Hiring the best people that help execute the data engineering vision within Blackbaud
- Establish recruiting pipeline for new team members through networking, internships, etc.
- Ensure that your teams are motivated, engaged and excited to do the work we do.
- Promote inquisitiveness within your teams
- Managing engineering teams work through other managers and directly
- Own the technical data governance practices and ensures data sovereignty, privacy, security and regulatory compliance.
- Independently identify and execute projects to improve the quality of life of engineers at Blackbaud
- Promote internally how data within Blackbaud can help change the world.
- Continuously challenging the status quo of how things have been done in the past.
- Other duties as assigned
We'd love to hear from you if:
- You have 8+ years of software and/or data engineering experience (specifically data focused or SaaS based products)
- You have 5+ years of experience managing 6+ person teams
- Strong understanding of Cloud Big Data and Pipeline services(Azure preferred)
- Expert in Big Data design patterns and implementation, as well as connected domains (real-time streaming, machine learning, etc.)
- Experience with Spark/Databricks that include Scala and Python
- Professional experience enabling Data Science with the proper data and platform
- Proven expertise in both batch and real-time processing models and tools
- Expertise in areas of data governance, privacy and regulation and professional experience with architectural approaches to data security
- Experience with continuous machine learning development and deployment
- Track record of teams successfully designing/building reliable, performant, scalable data platforms
- Have experience integrating multiple data sources into a common set of data assets or common data models
- Professional experience employing asynchronous, loosely coupled design patterns
- You are comfortable executing autonomously in the face of ambiguity
- You possess the growth mindset(“the code I just wrote should be rewritten”)