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Lead Data Engineer - AWS, Databricks & PySpark

ScolerTec Inc

**FULLY REMOTE**

ScolerTec is seeking Lead Data Engineer – AWS, Databricks & PySpark to design, build, and lead enterprise-scale cloud data engineering solutions.

This is a hands-on technical leadership role responsible for scalable ETL/ELT pipelines, batch and near-real-time data integration, lakehouse/data-platform implementation, cloud data services, CI/CD, data quality, governance, performance optimization, and technical direction of data engineers.

The ideal candidate has strong recent experience with AWS, Databricks, Apache Spark/PySpark, Python, SQL, Delta Lake, ETL/ELT, and technical leadership .

Key Responsibilities

  • Design and implement scalable cloud-based data platforms, including data lake, lakehouse, and data warehouse architectures.
  • Build enterprise-scale ingestion and ETL/ELT pipelines for batch and near-real-time workloads.
  • Develop data transformation and integration solutions using Python, SQL, Spark/PySpark, and modern cloud data technologies.
  • Implement Databricks/Delta Lake-based data engineering solutions and downstream curated/gold data layers.
  • Integrate pipelines with AWS compute, storage, messaging, and analytics services.
  • Lead technical design reviews, code reviews, engineering standards, and reusable data-engineering patterns.
  • Provide day-to-day technical guidance and mentoring to data engineers.
  • Implement data-quality checks, validation rules, error handling, observability, and pipeline monitoring.
  • Support streaming and event-driven data processing.
  • Implement Infrastructure as Code and CI/CD for repeatable data-platform and pipeline deployment.
  • Optimize pipeline performance, scalability, reliability, and cloud cost.
  • Support production incident resolution and root-cause analysis.
  • Partner with architecture, governance, migration, QA, DevSecOps, and security teams.
  • Maintain technical documentation, runbooks, and audit-ready engineering artifacts.

Qualifications

  • 7+ years of specialized data-engineering experience.
  • Strong hands-on experience building enterprise-scale data pipelines.
  • Strong production experience with AWS data and compute services.
  • Strong hands-on Databricks experience.
  • Strong Apache Spark/PySpark and Delta Lake experience.
  • Strong Python and SQL skills.
  • Strong ETL/ELT and data-transformation experience.
  • Experience with batch and streaming/near-real-time ingestion.
  • Experience with data orchestration tools.
  • Experience with CI/CD and Infrastructure as Code.
  • Experience with data quality, governance, metadata, and classification.
  • Proven technical leadership, design review, code review, and mentoring experience.
  • Federal, public-sector, or regulated-environment experience preferred.

Preferred Certifications

  • Databricks Certified Data Engineer Professional
  • AWS Certified Data Engineer
  • AWS Certified Solutions Architect – Professional
  • AWS Certified Data Analytics – Specialty
  • CDMP

Vacancy posted 2 hours ago
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