Cloud Leader-Data Migration ( Customer Engineering )

About Us

Responsibilities

• Solutioning and Consultation
• Data Architecture: Develop and implement comprehensive data architectures, including data warehouses, data lakes, and data lake houses, on Azure and GCP platforms.
• Data Modeling: Design and create data models that align with business requirements and support efficient data analysis and reporting.
• ETL/ELT: Develop and optimize ETL/ELT pipelines using tools like Databricks, Azure Data Factory, or GCP Data Fusion to extract, transform, and load data into various data stores.
• Data Warehousing: Design and implement scalable data warehouses on Azure Synapse Analytics or GCP BigQuery to support enterprise reporting and analytics.
• Data Lakehouses: Design and implement data lakehouses on Azure Databricks or GCP Dataproc to enable unified data management and analytics.
• Hadoop Ecosystem: Leverage Hadoop components (HDFS, MapReduce, Spark) for distributed data processing and analysis.
• Data Governance: Establish and maintain data governance policies and procedures to ensure data quality, security, and compliance.
• Scripting: Write scripts using languages like Python, SQL, or Scala to automate data tasks and integrate with other systems.
• Cloud Platform Expertise: Deep understanding of Azure and GCP cloud platforms, including their data services, storage options, and compute resources.
• Team Leadership: Mentor and Coach junior data architects and data engineers.
• Collaboration: Collaborate with business stakeholders, data analysts, and software developers to understand data requirements and deliver solutions.
  

Qualifications

• Bachelor's degree in Computer Science, Data Science, or a related field.
• 5+ years of experience in data architecture, data warehousing, and data lakehouse implementation.
• Strong proficiency in Azure and GCP data services, including Azure Synapse Analytics, Azure Databricks, GCP BigQuery, snowflake, databricks and GCP Dataproc.
• Expertise in ETL/ELT tools and techniques.
• Solid understanding of Hadoop components and distributed data processing.
• Proficiency in scripting languages like Python, SQL, and Scala.
• Experience with data governance and compliance frameworks.
• Excellent communication and collaboration skills.
• Ability to work independently and as part of a team.
  

Bonus Points

• Certifications in Azure Data Engineer Associate or GCP Data Engineer.
• Experience with real-time data processing and streaming technologies at scale.
• Knowledge of data governance, data security, and compliance frameworks.
• Experience with data visualization tools like Power BI, Tableau, or Looker.
• Familiarity with machine learning and artificial intelligence concepts.
• Knowledge of cloud-native data platforms and technologies.