Lead Data Engineer

The ideal candidate is a hands-on Senior/Lead Data Engineer with deep expertise in Databricks, PySpark, Python, SQL, and AWS. They have a proven track record building and optimizing scalable data pipelines, integrating data from multiple source systems including APIs, and deploying solutions using CI/CD tools such as Jenkins and Terraform. This person communicates clearly with both technical and business teams, can mentor junior engineers, and is comfortable working in a fast-paced environment involving data lakes, analytics platforms, and real-time streaming solutions. Experience with Salesforce Data Cloud, CRM Analytics, or Tableau is a strong plus.

To Succeed in This Role
Ability to define and design complex data integration solutions with general direction and stakeholder access
Capability to work independently and as part of a global, multi-faceted data warehousing and analytics team
Advanced knowledge of cloud-based data engineering and data warehousing solutions (AWS, Databricks, Snowflake)
Strong skills in RDBMS platforms (Oracle, SQL Server)
Familiarity with NoSQL platforms (MongoDB)
Strong understanding of data modeling, SQL, Python, and data engineering concepts
Knowledge of data quality, compliance, governance, and security principles
Proficiency in Python, SQL, and PySpark
Experience building data ingestion pipelines for structured and unstructured data
Ability to design and develop scalable data pipelines
Knowledge of cloud and on-prem contact center technologies (Salesforce, ServiceNow, Oracle CRM, Genesys Cloud/InfoMart, Calabrio Voice Recording, Nuance Voice Biometrics, IBM Chatbot, etc.) highly desirable
Experience with GitHub, JIRA, Confluence
Working experience with CI/CD processes (Jenkins, Terraform, Splunk, Dynatrace)
Highly innovative with strong systems thinking, design thinking, and process-simplification mindset
Detail-oriented with strong analytical, problem-solving, and organizational skills
Ability to communicate clearly with technical and business stakeholders
Knowledge of Informatica PowerCenter, Data Quality, and Data Catalog a plus
Knowledge of Agile methodologies a plus
Databricks Data Engineer Associate certification a plus

Data Engineer Requirements
Bachelor s degree in Computer Science, Information Technology, or a related field
8+ years of experience integrating and transforming contact center data into standardized, consumption-ready datasets with KPIs, supporting metrics, attributes, and enterprise hierarchies
Expertise in designing and deploying data integration solutions using web services with client-driven workflows and subscription features
Knowledge of mathematical foundations and statistical analysis
Strong interpersonal skills
Excellent communication and presentation skills
Advanced troubleshooting skills