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
Job source
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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