Senior Data Engineer / Databricks Specialist - US Citizens Only - Remote Role

Vinsys Information Technology, Inc
McLean, VA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Working hours
Regular working hours

Tech stack

Unity 3d Artificial Intelligence Amazon Web Services Amazon S3 Big Data Databases Continuous Integration Data Integrity Extract Transform Load (ETL) DevOps Apache Hive Identity and Access Management
+26 more
Job Scheduling Python (Programming Language) Machine Learning Performance Tuning Scrum Methodology Query Optimization Cloud Services SQL Databases Data Processing Apache Spark Software Troubleshooting Data Lakes Pyspark Gitlab-ci Semi-structured Data Machine Learning Operations Functional Programming Model Registry Restful APIs Terraform Data Pipelines Devsecops Jenkins Plan of Action and Milestones Databricks Web Api

Job description

  • Develop and optimize scalable Spark applications in AWS Databricks using Python, PySpark and SQL to support data processing and analytics needs.
  • Design, build and maintain robust ETL/ELT pipelines and implement Medallion Architecture (Bronze, Silver, Gold layers), ensuring data integrity, completeness and lineage.
  • Administer Databricks workspaces, including cluster provisioning, job scheduling, access controls, Unity Catalog and notebook management.
  • Manage AWS cloud infrastructure assets including S3, Lambda, IAM, Aurora and Glue, and provision environments using Terraform Infrastructure-as-Code (IaC).
  • Perform query optimization, performance tuning, troubleshooting and debugging for complex Spark jobs and large-scale data solutions.
  • Merge, consolidate and process structured, semi-structured and unstructured data sets from diverse API endpoints and databases.
  • Embed security gates and compliance controls within DevSecOps CI/CD pipelines (Jenkins, GitLab CI) to support FISMA/FedRAMP requirements, ATO reassessments and POA&M resolution.
  • Implement rigorous data quality controls, anomaly detection, validation rules and automated lineage tracking across all pipelines.
  • Collaborate within cross-functional Agile/Scrum teams in multi-contractor federal environments, providing technical leadership and production on-call support.

Requirements

Required experience and technical skills

  • Citizenship: U.S. citizenship required.
  • Mandatory certification: Active Databricks Certified Data Engineer Associate or Databricks Certified Data Engineer Professional.
  • Experience: 6+ years of dedicated hands-on experience in Databricks development.
  • Core big data stack: Production proficiency with PySpark, Spark SQL, Apache Spark and Delta Lake.
  • Cloud ecosystem: Strong experience in AWS Cloud services including S3, IAM, Lambda, Glue and Aurora.
  • Automation and DevOps: Production experience with Terraform (IaC) and CI/CD tools (Jenkins, GitLab CI or equivalent).
  • Languages and frameworks: Deep proficiency in Python and SQL; working knowledge of REST APIs for ingestion.
  • Clearance: Ability to obtain and maintain a Public Trust.
  • Methodology and education: Hands-on experience in Agile/Scrum delivery environments. Bachelor s degree in CS, IT, Data Science or a related engineering discipline., * Hands-on experience with Unity Catalog, Delta Live Tables (DLT) and AI/ML pipeline support (MLflow, Model Registry).
  • Experience in Federal Government contracting and compliance frameworks (FISMA / FedRAMP environments).
  • Active security clearance (Public Trust or higher).

Preferred certifications In addition to the mandatory Databricks Data Engineer certification, candidates holding any of the following will be prioritized:

  • Databricks Certified Machine Learning Associate
  • AWS Certified Solutions Architect Associate or Professional
  • AWS Certified Data Engineer Associate

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