Data Engineering Lead for Trusted Analytics

Aumni; Kentucky; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health care

On-site health centers

Retirement plan

Backup childcare

Tuition reimbursement

Mental health support

Financial coaching

Job summary

Next Frontier Capital seeks a Data Engineering Lead to build a high-quality measurement data foundation enabling trusted analytics at scale. You will design resilient datasets, pipelines, and reusable metrics across the PDLC, mentoring a small team and raising engineering standards.

You will work hands-on with SQL/dbt, Databricks, and PySpark, driving observability, data quality, and cost/performance. Collaboration with analytics, product, and engineering is essential for cross-functional

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 5+ years delivering production data solutions in a fast-paced engineering environment.
• Strong software engineering fundamentals (system design, data structures, OOP, testing strategies).
• Strong understanding of data modeling (conceptual, logical, physical).
• Hands-on experience with Databricks and large-scale distributed data processing/PySpark.
• Strong SQL skills and experience with modern transformation tooling (dbt).
• Experience designing and operating orchestration pipelines using Airflow (backfills, retries, monitoring).
• Demonstrated rigor building and maintaining trusted metrics and keeping them reliable as sources change.
• Ability to lead delivery in complex environments with multiple stakeholders and ambiguous requirements.

Responsibilities

• Design, build, and operate scalable data pipelines with SLAs and monitoring.
• Develop and curate trusted data products with clear ownership and documentation.
• Build and maintain metrics and datasets to measure AI adoption and productivity.
• Drive data quality and governance through validations, lineage, access controls, retention.
• Develop and operate Airflow workflows to schedule and monitor data movement.
• Model and transform data for analytics using SQL/dbt to support trusted reporting.
• Write production-grade Python/PySpark with testing and performance tuning.
• Partner with analytics, product, and engineering to define requirements and success criteria.
• Establish engineering best practices and continuously improve observability and cost.

Skills

Hands-on data engineering

SQL / dbt

Databricks

PySpark

Airflow

Data modeling

System design

Testing strategies

Leadership

Mentoring

Education

Bachelor’s degree in CS/Engineering

Tools

Airflow

dbt

Databricks

Spark/PySpark

Job description

Next Frontier Capital seeks a Data Engineering Lead to build a high-quality measurement data foundation enabling trusted analytics at scale. You will design resilient datasets, pipelines, and reusable metrics across the PDLC, mentoring a small team and raising engineering standards.

You will work hands-on with SQL/dbt, Databricks, and PySpark, driving observability, data quality, and cost/performance. Collaboration with analytics, product, and engineering is essential for cross-functional