Staff Data Engineer

Job title: Staff Data Engineer

Reports to: Director, Data Engineering

Department: Data Services

Location: Alpharetta, GA (Hybrid)

Grade: 19

About Priority: 

Priority Technology Holdings, Inc. is a leading financial technology company on a mission to deliver a personalized, easy-to-adopt financial toolset that accelerates cash flow and optimizes working capital for businesses. Our vision is to eliminate the barriers to unlocking revenue - empowering businesses to grow faster and operate smarter.

We achieve this through the Priority Commerce Engine, an innovative platform that combines payables, acquiring, and banking and treasury solutions. This unified approach allows businesses to streamline financial operations, reduce unnecessary costs, and uncover new revenue opportunities.

At Priority, we're driven by results. We expect our people to be known for results - bringing expertise, momentum, and relentless focus to every challenge, helping our clients and each other thrive.

About the Role:

As a Staff Data Engineer, you will play a pivotal role in our data infrastructure team. Your primary responsibilities include designing, developing, and implementing ETL data pipelines from diverse sources, ensuring their optimization and security. You'll collaborate closely with internal teams to identify and resolve operational challenges through the creation of data products, and you'll establish data marts for reliable and speedy data access. Your role also involves designing flexible API-based data services, implementing unit tests and monitoring systems to ensure data quality and efficiency, and working with data scientists, analysts, and stakeholders to fulfill data infrastructure needs. In addition to mentoring junior data engineers and advocating best practices within the team, you'll remain up-to-date with industry trends, technologies, and best practices in data engineering, introducing new tools and techniques to enhance the data platform's capabilities and efficiency. Your contributions will be essential in maintaining and advancing our data infrastructure.

Responsibilities: 

• Design, develop, and implement optimized and secure ETL data pipelines from various sources
• Collaborate with internal teams to identify and address operational challenges by designing and implementing data products
• Create data marts for reliable and fast data access
• Design flexible API-based data services
• Establish unit tests and monitoring systems for data quality and efficient correction operations
• Collaborate with data scientists, analysts, and stakeholders to meet data infrastructure needs
• Mentor junior data engineers and promote best practices within the team
• Stay updated on industry trends, technologies, and best practices in data engineering
• Introduce new tools and techniques to enhance the data platform’s capabilities and efficiency

What Success Looks Like:

In a Staff Data Engineer role, success is less about writing lots of code yourself and more about impact, leverage, and technical leadership.

• Enabling faster, more confident decisions through reliable data
• Supporting revenue, growth, or operational efficiency through data systems
• Translating business needs into durable technical solutions
• Ensuring data is trustworthy, discoverable, and well-defined
• Leading initiatives that span multiple teams or domains

Candidate Requirements:

• 8 years of hands-on technical experience in software development, data structures, and algorithms
• 2+ years of hands-on experience in Snowflake 
• 1 year of technical leadership experience, leading project teams and setting technical direction
• Strong analytical skills with a focus on collecting, organizing, and analyzing information with precision 
• Expertise in cloud platforms and services such as AWS (e.g., Redshift, Kinesis, EMR) or GCP (e.g., BigQuery, Dataflow, Pub/Sub)
• Proficiency in programming languages like Python, Node, Scala, or Go
• Proficiency in SQL and NoSQL databases including PostgreSQL, MySQL, MongoDB, and Cassandra.
• Staying updated with emerging data technologies, methodologies, and best practices
• Proven ability to work in a dynamic, fast-paced environment and manage multiple projects concurrently

Preferred Requirements:

• Proficient in big data tools: Spark, Kafka, etc
• Skilled in workflow tools like Airflow, AWS Step Function, etc
• Experienced in developing data solutions for payment processing
• Experience in designing