AWS Lead Data Engineer

Role: AWS Lead Data Engineer


Location: Roseland, NJ


Duration: Contract


As a Lead Data Engineer, you will spearhead the design and delivery of a data hub/marketplace aimed at providing curated client service data to internal data consumers, including analysts, data scientists, analytic content authors, downstream applications, and data warehouses. You will develop a service data hub solution that enables internal data consumers to create and maintain data integration workflows, manage subscriptions, and access content to understand data meaning and lineage. You will design and maintain enterprise data models for contact center-oriented data lakes, warehouses, and analytic models (relational, OLAP/dimensional, columnar, etc.). You will collaborate with source system owners to define integration rules and data acquisition options (streaming, replication, batch, etc.). You will work with data engineers to define workflows and data quality monitors. You will perform detailed data analysis to understand the content and viability of data sources to meet desired use cases and help define and maintain enterprise data taxonomy and data catalog. This role requires clear, compelling, and influential communication skills. You will mentor developers and collaborate with peer architects and developers on other teams.


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, especially AWS, Databricks, and/or Snowflake.
• Highly skilled in RDBMS platforms such as Oracle, SQLServer.
• Familiarity with NoSQL DB platforms like MongoDB.
• Understanding of data modeling and data engineering, including SQL and Python.
• Strong understanding of data quality, compliance, governance and security.
• Proficiency in languages such as Python, SQL, and PySpark.
• Experience in building data ingestion pipelines for structured and unstructured data for storage and optimal retrieval.
• Ability to design and develop scalable data pipelines.
• Knowledge of cloud-based and on-prem contact center technologies such as Salesforce.com, ServiceNow, Oracle CRM, Genesys Cloud, Genesys InfoMart, Calabrio Voice Recording, Nuance Voice Biometrics, IBM Chatbot, etc., is highly desirable.
• Experience with code repository and project tools such as GitHub, JIRA, and Confluence.
• Working experience with CI/CD (Continuous Integration & Continuous Deployment) process, with hands-on expertise in Jenkins, Terraform, Splunk, and Dynatrace.
• Highly innovative with an aptitude for foresight, systems thinking, and design thinking, with a bias towards simplifying processes.
• Detail-oriented with strong analytical, problem-solving, and organizational skills.
• Ability to clearly communicate with both technical and business teams.
• Knowledge of Informatica PowerCenter, Data Quality, and Data Catalog is a plus.
• Knowledge of Agile development methodologies is a plus.
• Having a Databricks data engineer associate certification is a plus but not mandatory.

Data Engineer Requirements:

• Bachelor's degree in computer science, information technology, or a similar field.
• 10+ years of experience integrating and transforming contact center data into standard, consumption-ready data sets incorporating standardized 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.