Data Engineer

New fulltime position open for a seasoned Data Engineer in the Lancaster, PA area!

All potential applicants are encouraged to scroll through and read the complete job description before applying.

This is an onsite role and not a remote based position.

Qualified applicants should currently be based in the greater Lancaster, PA area OR willing to relocate to this area.

Strong Databricks experience is required, along with advanced SQL skills.

US Citizenship or Permanent Resident status in the United States is a requirement for this position. Client is unable to transfer any visas including H1-B, F-1, C visas, etc.

Due to the large volume of applicants, candidates that send an email directly to with the following information will get first consideration

1. Current city/state in which you reside
2. Current citizenship status
3. Target salary range
4. Number of years working with Databricks on AWS
5. Your SQL skills rated on a 1-10 scale (1=novice, 10=expert)

Skills and background required:

• Bachelor's Degree preferred, or equivalent practical hands-on experience.
• A proven track record designing, delivering, and operating production-grade solutions in Databricks on AWS , including responsibility for architecture implementation, pipeline development, deployment, support, performance, and cost.
• >5 years of professional experience in data engineering, data platform engineering, analytics engineering, or similar.
• Proven experience delivering multiple end-to-end projects where engineered data products enabled sophisticated analysis - such as cross-system KPI reporting, forecasting, optimization, profitability analysis, anomaly detection, predictive modeling, scenario analysis, or AI/ML.
• Advanced SQL and strong Python/PySpark skills, including experience developing maintainable, tested, production-quality code for large and complex datasets.
• Strong knowledge of Spark, Delta Lake or comparable lakehouse patterns, dimensional and analytical data modeling, partitioning, schema evolution, data contracts, and performance tuning.
• Hands-on experience with core AWS data-platform capabilities such as S3, IAM, KMS, VPC networking, CloudWatch, Secrets Manager, and related services used to secure, integrate, and operate Databricks workloads.
• Experience building batch and incremental pipelines using APIs, files, databases, SaaS connectors, change data capture, and at least one orchestration framework or managed workflow capability.
• Experience with Git-based development, CI/CD, automated data testing, code review, environment management, and infrastructure-as-code practices. xhyhwjd
• Experience implementing data quality, observability, cataloging, lineage, access control, and operational support for business-critical data products.