Lead Engineer Data

Overview

Lead Data Engineer providing hands-on technical leadership in the design, development, and optimization of scalable data pipelines, ingestion frameworks, and data platforms, guiding technical decisions and mentoring engineers.

What you'll do

• Lead the design and implementation of advanced data pipelines and ingestion frameworks, personally developing, testing, and maintaining the underlying SQL, Python, and ETL code.
• Guide technical execution of complex data initiatives across teams, balancing production commitments with incremental modernization and deciding which processes to retain, migrate, redesign, or retire.
• Support and troubleshoot SAS Viya and SQL-based production workflows, tracing job failures and data discrepancies to root cause, implementing safe corrections, validating outputs, and improving monitoring and recovery.
• Translate highly complex business requirements into scalable data solutions, working with subject-matter experts to clarify business definitions and reconcile outputs into consistent, reusable datasets.
• Ensure data platforms are optimized for performance, scalability, and reliability, considering Snowflake query performance and compute cost.
• Enforce data governance, security, and quality standards.
• Mentor engineers and provide technical leadership on projects, sharing knowledge, documenting processes, and building backup ownership across the team.
• Lead code reviews and ensure adherence to engineering standards, using version control, automated testing, and CI/CD practices to support safe releases.
• Collaborate with architects and stakeholders to align solutions with enterprise direction, communicating technical decisions and production issues clearly to technical and nontechnical partners in a matrixed environment.
• Drive improvements in automation, efficiency, and platform capabilities.
• Support architectural discussions and contribute to design decisions, helping design Snowflake transformations, dimensional models, and shared analytics-ready data structures.
• Validate migrations through reconciliation, parallel runs, and rollback planning before retiring established workflows.
• Complete other duties as assigned.

What you'll need

• Bachelor's degree in Computer Science or related field, or equivalent combination of training and experience.
• 6–8+ years of data engineering experience with enterprise scale platforms.
• Advanced proficiency in SQL, including query optimization and complex transformations.
• Strong hands-on Python skills.
• Strong experience with AWS and modern data platforms.
• Hands-on Snowflake engineering experience.
• Deep understanding of data modeling, ETL/ELT processes, and data warehousing.
• Experience with dimensional modeling and reusable business-facing datasets.
• Demonstrated hands-on production support, persistence in resolving issues, and experience making safe changes to unfamiliar or complex existing code.
• Experience leading technical initiatives and mentoring engineers.
• Strong problem-solving and communication skills, with the ability to explain complex technical matters clearly, listen to business users, and collaborate constructively across teams.
• Experience working in Agile environments.
• Candidates with strong SQL, procedural programming, and enterprise ETL experience must be willing and able to learn and support SAS-based workflows.

Nice to have

• SAS/SAS Viya experience.
• PySpark experience.
• Experience preparing governed data for advanced analytics or machine learning.

Details

• Location: Nationwide Remote.
• Work environment: professional office environment.
• Applicants must be authorized to work for any employer in the U.S.; visa sponsorship, including CPT/OPT, is not available.
• Remote and hybrid positions require reliable high-speed wired internet from a fiber, cable, or DSL provider and a suitable home workspace; you may be required to work in the office if these are not available.
• Base salary range $125,400.00 - $181,875.00; non-sales positions may participate in a bonus program.