Lead Data Engineer- Onsite in Atlanta, GA- Locals Only

Title: Lead Data Engineer

Location: Atlanta, GA (Onsite)

Duration: 12 Months + extension

NOTE: Candidates on W2 only are encouraged to apply

An Lead Azure Data Engineer is responsible for designing, implementing, and maintaining the data infrastructure within an organization. They collaborate with both business and IT teams to understand stakeholders needs and unlock the full potential of data. They create conceptual and logical data models, analyze structural requirements, and ensure efficient database solutions.

Must Have Skills:
SAP Data Experience
Proficiency in Databricks and Azure Cloud, Databricks Asset Bundles, Hoslistic vision on the Data Strategy.
Proficiency in Data Streaming and Data Modeling
Experience in architecting at least two large-scale big data projects
Strong understanding of data scaling and its complexities
Data Archiving and Purging mechanisms.

Job Responsibilities:

Act as subject matter expert providing best-practice guidance on data lake and ETL architecture frameworks suitable for handling big data for unstructured and structured information.
Drive business and Service Layer development with the customer by finding new opportunities based on expanding existing solutions and creating new ones.
Provide hands-on subject matter expertise to build and implement Azure-based Big Data solutions.
Research, evaluate, architect, and deploy new tools, frameworks, and patterns to build sustainable Big Data platforms for our clients.
Facilitate and/or conduct requirements workshops.
Responsible for collaborating on the prioritization of technical requirements.
Collaborates with peer teams and vendors on the solution and delivery.
Has overall accountability for project delivery.
Works collaboratively with the Product Management, Data Management, and other Architects to deliver for the cloud data platform and Data as a Service.
Consults with clients to assess current problem states, define desired future states, define solution architecture, and make solutions recommendations.
Design and implement scalable and reusable data models to support analytical and operational use cases, ensuring compatibility with various business applications.
Optimize data models for performance and scalability, addressing key challenges in data latency, volume, and complexity in a big data environment.
Ensure data quality and consistency by establishing robust data validation and governance mechanisms during the modeling process.
Collaborate with data scientists, engineers, and business stakeholders to translate business requirements into effective and efficient data models.

Job Requirements:

Degree in computer science or equivalent preferred
Demonstrable experience in architecture, design, implementation, and/or support of highly distributed applications with Azure cloud and Databricks.
8+ Years of Hands-on experience with data modelling, database design, data mining, and segmentation techniques.
Working knowledge and experience with "Cloud Architectures" (e.g., SaaS, PaaS, IaaS) and the ability to address the unique security considerations of secure Cloud computing
Should have architected solutions for Cloud environments such as Microsoft Azure and/or Google Cloud Platform
Experience with debugging and performance tuning in distributed environments
Stronganalytical skillswith the ability to collect, organize, analyse, and broadcast significant amounts of information with attention to detail and accuracy
Experience dealing with structured, unstructured data.
Must have Python, PySpark experience.

Experience in ML or/and graph analysis is a plus