The Paylocity Data Practice is a cross-functional group comprised of Data Engineering and Data Warehousing, Data Science, Reporting and Data Insights. As a Senior Data Engineer under the Data Engineering team, you will play a pivotal role in designing, creating, deploying, and maintaining Paylocity’s data across different data entities and systems. You will demonstrate accountable ownership, unmitigated curiosity, a strong desire for continuous improvement while empowering, and mentoring team members to do the same.
Are you the teammate we are looking for?
During the first six months, you will:
- Perform data warehouse design, metadata and master data management, create and support the ETL process to extract the data from source systems, and into the data warehouse to support reporting and data science needs.
- Work closely with data analysts, data scientists, and other data consumers to meet business needs and also identify new unmet needs and implement solutions.
- Develop processes and procedures to build highly performant, resilient data processing pipelines, and secure data stores.
- Be involved in capacity planning for data warehouse servers on-prem and in the cloud.
- Create and implement effective metrics and monitoring processes.
- Produce and enforce industry-leading data engineering standards.
- Mentor and collaborate with other engineers on the team.
- Bachelor's degree in computer science, engineering, technology-related field, or equivalent experience.
- 7+ years of experience in data engineering while applying DWH/ETL best practices in traditional SQL (SQL Server, Oracle, Teradata) and/or big data environments (e.g., Hadoop, Spark, Hive
- 7+ years of experience with data modeling standards and data architecture.
- 7+ years of experience with Python/C#/Java development and software development principles.
- 5+ years of experience working on AWS, Azure, or GCP building data pipelines using data lakes, streaming, and serverless technologies.
- 3+ years in leading or mentoring other team members.
- Experience working in an agile and collaborative environment consisting of engineers, data analysts, data scientists, and other data consumers to build and optimize datasets to meet business requirements.
- Comfortable with enterprise systems architecture, distributed computing and logging (preferably ELK stack
- Experience with JIRA or other project management tool
- Experience and willingness to work on-call shifts as needed to support the team.
- Experience with web analytics tools such as Google Analytics or similar tool
- Knowledge of Kubernetes.
- Knowledge of NoSQL technologies.