Senior Data EngineerAPEI

The Senior Data Engineer designs, develops, and supports scalable data solutions that transform source data into reliable, reusable data assets for analytics, reporting, operational, and advanced analytics needs.

This role provides technical leadership across data modeling, transformation, performance, testing, deployment, and production support. The Senior Data Engineer works closely with data integration, architecture, analytics, governance, DevOps, and application teams to ensure data solutions are accurate, secure, maintainable, and aligned with enterprise standards.

The position is expected to lead complex engineering work, guide technical design decisions, review the work of other engineers, and improve data engineering practices across the organization.

KEY RESPONSIBILITIES:
• Design, build, test, deploy, and support scalable data pipelines, transformations, and reusable data models.
• Translate business and technical requirements into maintainable data structures and engineering solutions.
• Develop dimensional, relational, and analytical data models that support reporting, analytics, and downstream applications.
• Implement controls for data quality, reconciliation, lineage, testing, documentation, and production readiness.
• Optimize SQL, data models, workloads, and processing patterns for performance, reliability, scalability, and cost.
• Lead technical design reviews, code reviews, troubleshooting, root-cause analysis, and resolution of complex production issues.
• Partner with data integration, architecture, DevOps, security, governance, analytics, and application teams to deliver end-to-end data solutions.
• Establish and promote engineering standards for development, testing, deployment, documentation, monitoring, and source control.
• Evaluate source and downstream changes, identify technical risks, and communicate impacts to stakeholders and delivery teams.
• Mentor engineers, provide technical guidance, and contribute to the modernization and retirement of legacy data solutions.

POSITION REQUIREMENTS:
• Seven or more years of experience in data engineering, data warehousing, ETL/ELT development, database engineering, or a related field.
• Advanced SQL skills and demonstrated experience designing and supporting production data pipelines and analytical data models.
• Experience with cloud data platforms such as Snowflake, Azure, AWS, Google Cloud, Databricks, or comparable technologies.
• Experience with transformation and engineering tools such as dbt, Coalesce, Spark, SQL-based frameworks, or comparable platforms.
• Strong knowledge of dimensional modeling, data warehousing, incremental processing, orchestration, dependency management, and data quality testing.
• Experience with a programming or scripting language such as Python, PowerShell, Bash, Java, or Scala.
• Experience with Git-based source control, automated testing, CI/CD, deployment management, and production monitoring.
• Demonstrated ability to optimize data workloads, investigate complex issues, and design reliable recovery and reprocessing processes.
• Working knowledge of data security, access controls, sensitive data handling, lineage, governance, and regulatory requirements.
• Strong technical leadership, analytical, documentation, communication, mentoring, and cross-functional collaboration skills.

Education:

Bachelor's degree in computer science, information systems, data engineering, software engineering, information technology, or a related field. An equivalent combination of education and relevant professional experience may be considered.

Certifications:

Cloud-platform, database, data-engineering, or DevOps certifications are preferred but not required.

PROFESSIONAL EXPECTATIONS & COMPETENCIES:
• Collaborates: Builds and maintains effective partnerships with team members and stakeholders, working collaboratively to achieve shared goals and resolve challenges effectively.
• Communicates Effectively: Delivers clear, concise, and tailored communications through various modes (e.g., written, verbal, and visual) to meet the unique needs of diverse audiences.
• Customer Focus: Cultivates strong relationships with internal and external customers by actively listening to their needs and providing timely, customer-centric solutions.
• Demonstrates Self-Awareness: Regularly seeks and incorporate feedback from peers, leaders, and stakeholders to understand and address personal strengths and areas for growth.
• Ensures Accountability: Consistently meets deadlines and delivers on commitments, ensuring work quality and aligning with organizational standards.
• Innovation & Improvement: Encourages forward-thinking solutions, process improvements, and a culture of learning to enhance efficiency and team effectiveness.