Staff Data Engineer

 

As a Staff Data Engineer at Apptegy, you’ll have the opportunity to shape the future of our data strategy and infrastructure—not just build features. In this role, you’ll design and embed scalable, resilient data solutions that power user experiences across our product suite.

 

You’ll work alongside a talented and growing group of Staff+ engineers, helping to define the technical vision that guides the entire organization. This role is ideal for someone who thrives on solving complex challenges at the intersection of product, engineering, and analytics.

 

As a senior mentor, you’ll guide engineers, establish and champion data engineering best practices, and bring your strategic vision for data architecture to life. If you’re excited by the chance to make a lasting impact, influence technical direction at scale, and grow both your mentorship and technical expertise, we’d love for you to join us.

What You'll Do

• Lead the modernization, design, implementation, and maintenance of our data platform. This involves architecting a robust and scalable solution that seamlessly blends real-time and batch workloads.
• Own the architecture and development of end-to-end data pipelines. This includes ingesting diverse data from various Student Information System (SIS) partners, ensuring data hygiene, performing entity resolution, and distributing the processed data to downstream systems.
• Establish a single source of truth for all core data entities (e.g., Students, Staff, Guardians) and define a synchronization strategy to ensure data integrity and consistency across all Apptegy products and services.
• Define and enforce data quality, security, privacy, and governance standards, implementing automated data profiling, cleansing, and validation processes to ensure the accuracy, completeness, and timeliness of our data.
• Act as a technical mentor and a force multiplier for the engineering unit, setting best practices and technical standards for data engineering, modeling, and pipeline development.
• Partner with product, engineering, and customer success teams to understand business requirements and translate them into scalable data solutions and accessible data assets.

What You'll Bring

• A Bachelor's or Master's degree in Computer Science, Statistics, Informatics, Information Systems, or a related quantitative field, or equivalent experience with 8+ years of experience in software engineering or data engineering, with at least 3 years in a senior or staff-level role.
• Proven experience at the Staff or Principal level in a data engineering or related technical role.
• Demonstrated success in designing and implementing complex, end-to-end data platforms.
• Expertise in Python, SQL, and other relevant languages for data manipulation and automation. 
• Experience with data streaming frameworks such as Kafka and Kinesis to provide realtime data ingestion and distribution.
• Strong knowledge of data architecture, data modeling, data warehousing and entity resolution concepts.
• Extensive hands-on experience designing and building complex data pipelines and ETL/ELT processes for various data types and volumes for both analytical and operational systems.
• Expertise in designing and implementing complex data distribution and synchronization strategies across loosely coupled services or microservices architectures.
• Demonstrated ability to lead technical conversations and collaborate with various stakeholders.
• Exceptional problem-solving skills and a proactive, analytical mindset.

What Helps You Stand Out

• Prior experience with K-12 district and school data systems, particularly Student Information Systems (SIS), such as PowerSchool, Infinite Campus, or Skyward.
• Experience in the B2B SaaS industry.
• Experience with AirFlow and DBT.
• Familiarity with event-driven architectures and messaging services.
• Familiarity with AWS cloud services relevant to data engineering (e.g., EC2, RDS, Aurora Serverless, SQS, Lambda).
• Familiarity with SnowflakeProficiency or at least exposure to Ruby on RailsFamiliarity with data pipeline, workflow management, and ETL tools like CloverDX
• Contributions to open-source data projects or engineering communities.