Data Architect (Hybrid)

Location: Atlanta, GA (Hybrid)

Mode of Interview: Phone + Skype

Job Description:

Must have 7+ years of experience in the following:



-Experience in SDLC with key emphasis on BigData Technologies like Spark, Scala, Spark Mlib, Hadoop, Cassandra etc

-Experience in Data Warehouse Architecture and Designing Star, Snow flake Schema, Fact and Dimension tables, Physical and Logical data modelling using tools like Erwin, ER Studio etc

-Extensive experience in data modelling, data architecture, solution architecture and master data concepts and business intelligence to design and build state of art data warehouses, data marts, and data lakes

-Hands-on experience with Big Data technologies and frameworks on Azure cloud - Data Factory, Databricks, Python, Spark SQL, PySpark SQL, Azure SQL, SSIS, Logic App, Linked Services, Azure ML Studio, Triggers, Rest API's, Power Bi and Git etc

-Experience in developing and implementing data governance policies and procedures, including data quality, data privacy, and data retention.

-Must have experience in evaluating new and emerging technologies related to data management, and making recommendations on their adoption and implementation.

-Familiar with machine learning/deep learning framework, include R, sklearn and Tensorflow

-Knowledge of project management methodology(e.g. Agile, DevOps, Mic service)







Responsibilities



-Data Modeling & Design: Defining the structure and format of data within the organization, including data models, data dictionaries, and data standards, domain data modelling.

-Data Architecture: defining end to end solutions for BigData Products using Agile working methodologies for MVP's, POC's etc. Architecture is optimized fro large datasets acquisition, analysis, storage, cleansing, transformation and visualization

-Data Integration: Ensuring that data is integrated and available to all relevant systems and applications, and that data flows seamlessly to the datalake and associated ecosystem

-Data Security: Establishing data security policies and procedures, and ensuring that data is protected against unauthorized access, data breaches, and other security threats.

-Data Governance: Defining policies and procedures for managing data, including data quality, data privacy, and data retention.

-Data Strategy: Developing and implementing a data strategy that aligns with the organization's overall business objectives.

-Technology Evaluation: Evaluating new and emerging technologies related to data management, and making recommendations on their adoption and implementation.