Lead Data Engineer (Databricks)

HMG America
United States
7 days ago
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Role details

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

Tech stack

Amazon Web Services Amazon S3 Data Analysis Audit Trail Microsoft Azure Batch Processing Cloud Database Cluster Analysis Information Technology Consulting Continuous Integration Data Architecture Information Engineering
+31 more
Data Governance Data Warehousing DevOps Github Apache Hadoop High-Level Architecture Apache Hive Identity and Access Management Python (Programming Language) Performance Tuning SQL Databases Data Streaming Teradata SQL Netezza Snowflake Apache Spark Infrastructure as Code (IaC) Cloudformation Servicebus Data Lakes Pyspark Information Technology Data Lineage AWS Glue AWS Data Analytics Data Management Functional Programming Terraform Jenkins Amazon Redshift Databricks

Job description

We are seeking an experienced Lead Data Engineer (Databricks) with a strong background in IT consulting and professional services to lead end-to-end cloud data enterprise initiatives. In this role, you will act as a trusted technical advisor to client stakeholders while leading the architecture, design, and execution of scalable Lakehouse platforms on AWS using Databricks.

The ideal candidate possesses exceptional client engagement abilities, deep hands-on expertise with the Databricks Medallion Architecture, Unity Catalog, and Delta Live Tables (DLT), along with a proven track record of migrating legacy data warehouses to modern AWS data ecosystems., 1. Solution Architecture & Technical Leadership

  • Lakehouse Architecture: Architect, design, and implement scalable, enterprise-grade data platforms on AWS using the Databricks Lakehouse architecture.
  • Medallion Architecture: Establish robust data architecture patterns across Bronze, Silver, and Gold layers for both real-time streaming and batch processing pipelines.
  • Data Governance & Security: Implement fine-grained access control, governance, data lineage, and audit trails using Databricks Unity Catalog, AWS IAM, and KMS.
  • Performance & Cost Optimization: Optimize cluster configurations, auto-scaling parameters, and Delta Lake performance techniques (Z-Ordering, Liquid Clustering, compaction).
  • Ecosystem Integration: Seamlessly integrate AWS-native services (S3, AWS Glue, Lambda, EventBridge, Redshift, Athena, Secrets Manager) with Databricks.
  1. Client Engagement & Strategic Advisory (Consulting) * Stakeholder Management: Lead discovery workshops, technical assessments, and architecture reviews with C-level executives, VPs of Engineering/Data, and Enterprise Architects. * Technical Roadmaps: Translate complex business requirements into solution blueprints, high-level architecture diagrams, technical roadmaps, and Statements of Work (SOWs). * Legacy Modernization: Drive client migration strategies from legacy data warehouses (e.g., Teradata, Netezza, Snowflake, On-Prem Hadoop) to AWS Databricks. * Best Practices Guidance: Educate clients on cloud data best practices, FinOps/cost optimization strategies, and modern Lakehouse paradigms.

  2. Team Leadership, CI/CD & DevOps * Technical Mentorship: Guide, direct, and mentor cross-functional teams of Data Engineers, Analytics Engineers, and DevOps Engineers. * Infrastructure as Code (IaC): Enforce IaC best practices using Terraform or CloudFormation for automated enterprise workspace and cluster deployments. * DevOps & Automation: Build and maintain CI/CD pipelines for Databricks notebooks, Delta Live Tables (DLT), and Spark jobs across multi-environment setups (Dev, Test, Prod).

Requirements

  • Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Technology, or a related field.
  • Technical Expertise:
  • 8+ years in Data Engineering with at least 3+ years in a Lead/Architect capacity.
  • Deep experience with Databricks, PySpark/Scala, Delta Lake, Unity Catalog, and Delta Live Tables (DLT).
  • Hands-on experience with AWS Cloud Data Ecosystem (S3, Glue, Lambda, EMR, Redshift, IAM).
  • Proficiency in Python, SQL, and Spark SQL performance tuning.
  • Strong experience with Infrastructure-as-Code (Terraform) and CI/CD tools (GitHub Actions, Azure DevOps, Jenkins).
  • Consulting & Soft Skills:
  • Exceptional verbal and written communication skills with the ability to articulate complex technical ideas to executive audiences.
  • Strong problem-solving skills and client-facing advisory experience.

About the company

HMG America LLC is the best Business Solutions focused Information Technology Company with IT consulting and services, software and web development, staff augmentation and other professional services. One of our direct clients is looking for Lead Data Engineer (Databricks) in Remote. Below is the detailed job description.

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