As a Database Engineer, you will be responsible for the following:
- Building and maintaining scalable data pipelines and infrastructure that support analytics, business intelligence, and data integration initiatives.
- Ensures efficient and reliable access to data across the organization by designing robust data models, optimizing data workflows, and implementing data quality and governance practices.
- Collaborate with stakeholders across the organization to translate business requirements into robust technical solutions while adhering to established best practices, security standards, and regulatory requirements
Salary Range:
This is a non-exempt position. The starting salary range is: Level I: $86,[redacted]9 - $107,960.35, Level II: $106,414.36 - $133,017.95, Level III $131,113.13 - $163,891.42, Senior: $131,113.13 - $163,891.42 however, actual placement within the range will be determined individually based on your experience relative to organizational needs and internal salary equity.
Schedule:
Normally works a weekday schedule, but may be required to work evenings, holidays, or weekends. May be required to travel overnight with or without notice. Could be subjected to on-call status.
Education/Experience:
A bachelor's degree in computer science, information systems, business analytics, applied statistics, or a related field for all levels is required. A master's degree in computer science, information systems, computer engineering, artificial intelligence, machine learning, data science, or a closely related field is preferred at the Senior level.
Certificates, Licenses, Registrations:
- Incumbent Bonding REQUIRED by TFCU's chosen authority.
- Certifications such as Microsoft Certified: Azure Data Engineer Associate or Fabric Analytics Engineer Associate are preferred for Data Engineer III and Senior Data Engineer.
Keys to success:
In order to be successful as a
Database Engineer you must possess these qualifications:
- Strong interpersonal and team collaboration skills.
- Ability to communicate technical concepts effectively to technical and non-technical audiences.
- Strong analytical and problem-solving skills with the ability to design scalable, efficient, and reliable data solutions.
- Strong understanding of data structures, algorithms, and core data engineering principles.
- Detail-oriented with the ability to maintain accurate technical documentation, data lineage, and metadata.
- Ability to manage multiple projects, priorities, and deadlines in a dynamic environment.
- Proficiency in SQL and Python; experience with Apache Spark, Scala, or Java preferred.
- Strong understanding of data modeling, database design, and dimensional modeling techniques, including star and snowflake schemas.
- Experience with Microsoft Fabric technologies, including Data Factory, Dataflows Gen2, Synapse, OneLake, and Power BI (Level II and above).
- Knowledge of source control, CI/CD pipelines, and DevOps practices supporting data engineering solutions (Level II and above).
- Knowledge of data governance, information security, privacy, and regulatory requirements, including data classification, encryption, GLBA, and protection of personally identifiable information (PII).
- Advanced knowledge of cloud-based data platforms, semantic modeling, data architecture, and real-time data processing technologies (Senior Data Engineer).
