Job Seekers, Please send resumes to resumes@hireitpeople.com
Must have 7+ years of experience in the following:
- Must have in depth Azure Cloud
- 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 APIs, 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)
Job 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 MVPs, POCs 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 organizations overall business objectives.
- Technology Evaluation: Evaluating new and emerging technologies related to data management, and making recommendations on their adoption and implementation.
Education:
- Bachelors or Masters Degree (accredited school) with emphasis in:
- Computer/Information Science / Information Technology Engineering / Management Information System (MIS)
